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Journal articles on the topic 'Limited label availability'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Maiti, A., S. J. Oude Elberink, and G. Vosselman. "EFFECT OF LABEL NOISE IN SEMANTIC SEGMENTATION OF HIGH RESOLUTION AERIAL IMAGES AND HEIGHT DATA." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-2-2022 (May 17, 2022): 275–82. http://dx.doi.org/10.5194/isprs-annals-v-2-2022-275-2022.

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Abstract. The performance of deep learning models in semantic segmentation is dependent on the availability of a large amount of labeled data. However, the influence of label noise, in the form of incorrect annotations, on the performance is significant and mostly ignored. This is a big concern in remote sensing applications, wherein acquired datasets are spatially limited, labeling is done by domain experts with possible sources of high inter-and intra-observer variability leading to erroneous predictions. In this paper, we first simulate the label noise while conducting experiments on two di

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Hu, Han, Yang Lei, Daisy Xin, et al. "2D Label Free Microscopy Imaging Analysis Using Machine Learning." Electronic Imaging 2020, no. 14 (2020): 341–1. http://dx.doi.org/10.2352/issn.2470-1173.2020.14.coimg-341.

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Separation and isolation of living cells plays an important role in the fields of medicine and biology with label-free imaging often used for isolating cells. The analysis of label-free cell images has many challenges when examining the behavior of cells. This paper presents methods to analyze label-free cells. Many of the tools we describe are based on machine learning approaches. We also investigate ways of augmenting limited availability of training data. Our results demonstrate that our proposed methods are capable of successfully segmenting and classifying label-free cells.

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Liu, Jun, Qianwen Zhang, Joseph Masabni, and Genhua Niu. "Low Nitrogen Availability in Organic Fertilizers Limited Organic Watermelon Transplant Growth." Horticulturae 10, no. 11 (2024): 1140. http://dx.doi.org/10.3390/horticulturae10111140.

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Fertilization guidelines for organic watermelon transplant production are rare. We investigated the effect of four commercial organic fertilizers and seven organic fertilizer blends, along with one conventional fertilizer (Peter’s Professional 20-20-20) on watermelon transplants. The four organic fertilizers were Nature Safe (fertilizer label: 7-7-7), Miracle-Gro (8-8-8), Dr. Earth fertilizer tea (4-4-4), and Drammatic (2-4-1). The seven blended organic fertilizers were created by supplementing Drammatic with nitrogen (N)-rich and/or potassium (K)-rich fertilizers to balance its N:phosphorus (

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Id, Ibnu Daqiqil, Pardomuan Robinson Sihombing, and Supratman Zakir. "Handling concept drifts and limited label problems using semi-supervised combine-merge Gaussian mixture model." Bulletin of Electrical Engineering and Informatics 10, no. 6 (2021): 3361–68. http://dx.doi.org/10.11591/eei.v10i6.3259.

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When predicting data streams, changes in data distribution may decrease model accuracy over time, thereby making the model obsolete. This phenomenon is known as concept drift. Detecting concept drifts and then adapting to them are critical operations to maintain model performance. However, model adaptation can only be made if labeled data is available. Labeling data is both costly and time-consuming because it has to be done by humans. Only part of the data can be labeled in the data stream because the data size is massive and appears at high speed. To solve these problems simultaneously, we a

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Griffiths, Melda, Jacky Boivin, Eryl Powell, and Lewis Bott. "Evaluating source credibility effects in health labelling using vending machines in a hospital setting." PLOS ONE 19, no. 2 (2024): e0296901. http://dx.doi.org/10.1371/journal.pone.0296901.

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Objectives Providing advice to consumers in the form of labelling may mitigate the increased availability and low cost of foods that contribute to the obesity problem. Our objective was to test whether making the source of the health advice on the label more credible makes labelling more effective. Methods and measures Vending machines in different locations were stocked with healthy and unhealthy products in a hospital. Healthy products were randomly assigned to one of three conditions (i) a control condition in which no labelling was present (ii) a low source credibility label, “Lighter choi

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Han, Yucheng, Na Zhao, Weiling Chen, Keng Teck Ma, and Hanwang Zhang. "Dual-Perspective Knowledge Enrichment for Semi-supervised 3D Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (2024): 2049–57. http://dx.doi.org/10.1609/aaai.v38i3.27976.

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Semi-supervised 3D object detection is a promising yet under-explored direction to reduce data annotation costs, especially for cluttered indoor scenes. A few prior works, such as SESS and 3DIoUMatch, attempt to solve this task by utilizing a teacher model to generate pseudo-labels for unlabeled samples. However, the availability of unlabeled samples in the 3D domain is relatively limited compared to its 2D counterpart due to the greater effort required to collect 3D data. Moreover, the loose consistency regularization in SESS and restricted pseudo-label selection strategy in 3DIoUMatch lead t

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Zitzmann, Franziska D., Sabine Schmidt, and Heinz-Georg Jahnke. "Blick ins Innere: Analyse von 3D-Kulturen mittels Mikrokavitätenarrays." BIOspektrum 30, no. 4 (2024): 456–59. http://dx.doi.org/10.1007/s12268-024-2224-8.

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AbstractThree-dimensional cultures are a big step towards a more accurate mimicry of the in vivo environment. Given the limited availability of non-invasive analysis methods, especially beyond 2D cultures, we have developed a platform for multimodal bioelectronic monitoring in combination with our microcavity array technology for label-free real-time analysis of 3D cultures. This allows a wide range of cell-specific processes and drug responses to be studied with enhanced spatial resolution and in an automated setting.

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Ran, Shuhao, Gang Ma, Fudong Chi, Wei Zhou, and Yonghong Weng. "HPM-Match: A Generic Deep Learning Framework for Historical Landslide Identification Based on Hybrid Perturbation Mean Match." Remote Sensing 17, no. 1 (2025): 147. https://doi.org/10.3390/rs17010147.

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The scarcity of high-quality labeled data poses a challenge to the application of deep learning (DL) in landslide identification from remote sensing (RS) images. Semi-supervised learning (SSL) has emerged as a promising approach to address the issue of low accuracy caused by the limited availability of high-quality labels. Nevertheless, the application of SSL approaches developed for natural images to landslide identification encounters several challenges. This study focuses on two specific challenges: inadequate information extraction from limited unlabeled RS landslide images and the generat

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Ding, Chen, Yu Li, Yue Wen, et al. "Boosting Few-Shot Hyperspectral Image Classification Using Pseudo-Label Learning." Remote Sensing 13, no. 17 (2021): 3539. http://dx.doi.org/10.3390/rs13173539.

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Deep neural networks have underpinned much of the recent progress in the field of hyperspectral image (HSI) classification owing to their powerful ability to learn discriminative features. However, training a deep neural network often requires the availability of a large number of labeled samples to mitigate over-fitting, and these labeled samples are not always available in practical applications. To adapt the deep neural network-based HSI classification approach to cases in which only a very limited number of labeled samples (i.e., few or even only one labeled sample) are provided, we propos

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Roth, Myron. "The availability and use of chemotherapeutic sea lice control products." Contributions to Zoology 69, no. 1-2 (2000): 109–18. http://dx.doi.org/10.1163/18759866-0690102012.

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An international survey revealed that eleven compounds representing five pesticide types are currently being used on commercial salmon farms for sea lice control. These include two organophosphates (dichlorvos and azamethiphos); three pyrethrin/pyrethroid compounds (pyrethrum, cypermethrin, deltamethrin); one oxidizing agent (hydrogen peroxide); three avermectins (ivermectin, emamectin and doramectin) and two benzoylphenyl ureas (teflubenzuron and diflubenzuron). The number of compounds available in any one country is highly variable, ranging from 9 (Norway) to 6 (Chile, United Kingdom) to 4 (

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Virág, Dávid, Gitta Schlosser, Adina Borbély, et al. "A Mass Spectrometry Strategy for Protein Quantification Based on the Differential Alkylation of Cysteines Using Iodoacetamide and Acrylamide." International Journal of Molecular Sciences 25, no. 9 (2024): 4656. http://dx.doi.org/10.3390/ijms25094656.

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Mass spectrometry has become the most prominent yet evolving technology in quantitative proteomics. Today, a number of label-free and label-based approaches are available for the relative and absolute quantification of proteins and peptides. However, the label-based methods rely solely on the employment of stable isotopes, which are expensive and often limited in availability. Here we propose a label-based quantification strategy, where the mass difference is identified by the differential alkylation of cysteines using iodoacetamide and acrylamide. The alkylation reactions were performed under

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Fishman, Michael A., Ashley Scherer, Jacob Topfer, and Philip S. H. Kim. "Limited Access to On-Label Formulations of Buprenorphine for Chronic Pain as Compared with Conventional Opioids." Pain Medicine 21, no. 5 (2019): 1005–9. http://dx.doi.org/10.1093/pm/pnz197.

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Abstract Importance Buprenorphine is a Schedule III analgesic that is recommended as the firstline long-acting opioid for the treatment of chronic pain due to its ceiling effect on respiratory depression, adverse effect profile, and analgesic efficacy. However, prescription drug coverage policies commonly require that patients try and fail multiple Schedule II conventional opioids before approval of on-label use of buprenorphine for chronic pain. Design A retrospective review was performed looking at coverage of buprenorphine in the forms of Butrans and Belbuca. Patient denial letters, web sea

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Rejman, Krystyna, Joanna Kaczorowska, Ewa Halicka, and Aleksandra Prandota. "How Do Consumers Living in European Capital Cities Perceive Foods with Sustainability Certificates?" Foods 12, no. 23 (2023): 4215. http://dx.doi.org/10.3390/foods12234215.

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Certification aims at ensuring food quality and safety, as well as confirming other beneficial credence attributes, such as local origin and sustainability. In order to explore the visibility and credibility of such certification labels functioning in the European Union, a study was conducted among residents of two EU Member States, Poland and Belgium. Face-to-face questionnaire-based interviews and focus group interviews were conducted among 701 adults living in Warsaw and Brussels—the capital cities of these countries. Almost 44% of Belgian respondents and 33% of Polish respondents considere

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Zhu, Hongbo, Tao Yu, Xiaofei Mi, et al. "Large-Scale Land Cover Mapping Framework Based on Prior Product Label Generation: A Case Study of Cambodia." Remote Sensing 16, no. 13 (2024): 2443. http://dx.doi.org/10.3390/rs16132443.

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Large-Scale land cover mapping (LLCM) based on deep learning models necessitates a substantial number of high-precision sample datasets. However, the limited availability of such datasets poses challenges in regularly updating land cover products. A commonly referenced method involves utilizing prior products (PPs) as labels to achieve up-to-date land cover mapping. Nonetheless, the accuracy of PPs at the regional level remains uncertain, and the Remote Sensing Image (RSI) corresponding to the product is not publicly accessible. Consequently, the sample dataset constructed through geographic l

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Gemma, Pantaleo, Eleonora Nannoni, Barbara Padalino, et al. "Perception and Awareness of Animal Welfare Among Residents of Malta." Animals 15, no. 11 (2025): 1634. https://doi.org/10.3390/ani15111634.

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A representative sample of Maltese citizens (N = 384) was surveyed about their perception and attitude towards animal welfare and animal-friendly foods. Knowledge about animal welfare was self-evaluated as moderate (36%) or good (27%), and mass media (television, web and newspapers) were the primary information source (73%). Dairy cows were perceived as having the highest welfare (average rating 3 on a 1-to-5 scale), while conditions for broilers and pigs were perceived as more critical (average rating 2.7). Respondents consider animal welfare important (64%), the availability of welfare-frien

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Rehmani, Muhammad Asif Ali, Saad Aslam, Shafiqur Rahman Tito, et al. "Power Profile and Thresholding Assisted Multi-Label NILM Classification." Energies 14, no. 22 (2021): 7609. http://dx.doi.org/10.3390/en14227609.

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Next-generation power systems aim at optimizing the energy consumption of household appliances by utilising computationally intelligent techniques, referred to as load monitoring. Non-intrusive load monitoring (NILM) is considered to be one of the most cost-effective methods for load classification. The objective is to segregate the energy consumption of individual appliances from their aggregated energy consumption. The extracted energy consumption of individual devices can then be used to achieve demand-side management and energy saving through optimal load management strategies. Machine lea

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Umirzakova, Sabina, Shakhnoza Muksimova, Abrayeva Mahliyo Olimjon Qizi, and Young Im Cho. "Lightweight Transformer with Adaptive Rotational Convolutions for Aerial Object Detection." Applied Sciences 15, no. 9 (2025): 5212. https://doi.org/10.3390/app15095212.

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Oriented object detection in aerial imagery presents unique challenges due to the arbitrary orientations, diverse scales, and limited availability of labeled data. In response to these issues, we propose RASST—a lightweight Rotationally Aware Semi-Supervised Transformer framework designed to achieve high-precision detection under fully and semi-supervised conditions. RASST integrates a hybrid Vision Transformer architecture augmented with rotationally aware patch embeddings, adaptive rotational convolutions, and a multi-scale feature fusion (MSFF) module that employs cross-scale attention to e

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Zhao, Jiaguo, Junjie Zhang, Huaxi Huang, and Jian Zhang. "Enhancing Semi-Supervised Few-Shot Hyperspectral Image Classification via Progressive Sample Selection." Remote Sensing 16, no. 10 (2024): 1747. http://dx.doi.org/10.3390/rs16101747.

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Hyperspectral images (HSIs) provide valuable spatial–spectral information for ground analysis. However, in few-shot (FS) scenarios, the limited availability of training samples poses significant challenges in capturing the sample distribution under diverse environmental conditions. Semi-supervised learning has shown promise in exploring the distribution of unlabeled samples through pseudo-labels. Nonetheless, FS HSI classification encounters the issue of high intra-class spectral variability and inter-class spectral similarity, which often lead to the diffusion of unreliable pseudo-labels duri

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San Giovanni, Christine B., Brooke Sweeney, Joseph A. Skelton, Megan M. Kelsey, and Aaron S. Kelly. "Aversion to Off-label Prescribing in Clinical Pediatric Weight Management: The Quintessential Double Standard." Journal of Clinical Endocrinology & Metabolism 106, no. 7 (2021): 2103–13. http://dx.doi.org/10.1210/clinem/dgab276.

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Abstract Context Pediatric obesity is now recognized as a chronic disease; yet few treatment options exist besides lifestyle modification therapy and bariatric surgery. We describe the limited availability of United States Food and Drug Administration (FDA)–approved antiobesity medications for adolescents and compare this to what is available for adults. We offer a rationale for off-label prescribing to assist with lifestyle modification therapy. We also highlight the need for more pharmacotherapy options and additional research into novel treatments for pediatric obesity. Case Description We

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Kopp, Lisa M., Kathylynn Saboda, Bhuvana Setty, et al. "Off label targeted therapy use in adolescents and young adults with sarcoma." Journal of Clinical Oncology 37, no. 15_suppl (2019): e21504-e21504. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e21504.

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e21504 Background: Outcomes for patients with metastatic or recurrent sarcomas remains dismal with < 20% overall survival. Due to the rarity of sarcomas, the development, testing, and approval of new therapies takes years. Most early phase clinical trials are restricted to adults leaving young patients with limited options. Little is known about the prevalence and clinical characteristics of patients receiving off-label targeted therapy (OLTT). In this multi-institutional retrospective review we evaluated OLTT use in this population. Methods: Patients with recurrent sarcoma diagnosed betwee

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Kim, R. B. "A multi-attribute model of Japanese consumer's purchase intention for GM foods." Agricultural Economics (Zemědělská ekonomika) 56, No. 10 (2010): 449–59. http://dx.doi.org/10.17221/113/2009-agricecon.

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This study illustrates that consumers' GM food purchase decision is determined by a set of correlated variables. The interrelationship among the GM food purchase decision determinants is examined conceptually and empirically with a multi-attribute model, describing this interrelationship. Consumers' attitudes toward subjects such as innovation, science &amp; technology as well as their trust towards the government's regulatory system of food safety and GM food are strong indicators of the consumers' GM food purchase decision. Given the limited availability of GM foods in the market which l

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Mo, Tingyu, Jacqueline C. K. Lam, Victor O. K. Li, and Lawrence Y. L. Cheung. "DECT: Harnessing LLM-assisted Fine-Grained Linguistic Knowledge and Label-Switched and Label-Preserved Data Generation for Diagnosis of Alzheimer’s Disease." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 23 (2025): 24885–92. https://doi.org/10.1609/aaai.v39i23.34671.

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Alzheimer’s Disease (AD) is an irreversible neurodegenerative disease affecting 50 million people worldwide. Low-cost, accurate identification of key markers of AD is crucial for timely diagnosis and intervention. Language impairment is one of the earliest signs of cognitive decline, which can be used to discriminate AD patients from normal control (NC) individuals. Patient-interviewer dialogues may be used to detect such impairments, but they are often mixed with ambiguous, noisy, and irrelevant information, making the AD detection task difficult. Moreover, the limited availability of AD spee

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Putri, Karisma Amalinda, and Susmono Widagdo. "Meningkatkan Daya Tarik Restoran dengan Kuliner Halal : Strategi Menu di Hotel Yamamomo Awakankou, Jepang." KIRYOKU 8, no. 2 (2024): 435–45. https://doi.org/10.14710/kiryoku.v8i2.435-445.

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Yamamomo Restaurant at Awakanko Hotel is currently facing challenges in meeting customer demands for halal menu options. One of the reasons for the limited variety of halal menus is the restricted availability of ingredients, which are only accessible during certain periods. This has led to complaints from customers. This study aims to analyze the strategies of Yamamomo's management in increasing the variety and availability of halal menus as an effort to enhance the restaurant's appeal, meet customer demands, and improve their satisfaction. The method used is qualitative, analyzing management

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Lisi, Donna M. "Specific Prescribing Information for Geriatric Use in the 2019 Product Labeling for Novel New Drug Approvals." Senior Care Pharmacist 36, no. 9 (2021): 455–65. http://dx.doi.org/10.4140/tcp.n.2021.455.

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Objectives To review the availability of information specific to older people in the product labeling for novel US Food and Drug Administration drug approvals in 2019. Design Descriptive report. Methods Product labeling for the 48 novel new drugs approved by the US Food and Drug Administration in 2019 were analyzed for the presence of information specific to older people. The “Geriatric Use” section, Section 8.5 in the product labeling, was categorized based on the information available. Each product label was further searched using the terms “geriatric,” “elderly,” “old,” and “year.” Searches

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Ma, Zhen, José J. M. Machado, and João Manuel R. S. Tavares. "Weakly Supervised Video Anomaly Detection Based on 3D Convolution and LSTM." Sensors 21, no. 22 (2021): 7508. http://dx.doi.org/10.3390/s21227508.

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Weakly supervised video anomaly detection is a recent focus of computer vision research thanks to the availability of large-scale weakly supervised video datasets. However, most existing research works are limited to the frame-level classification with emphasis on finding the presence of specific objects or activities. In this article, a new neural network architecture is proposed to efficiently extract the prominent features for detecting whether a video contains anomalies. A video is treated as an integral input and the detection follows the procedure of video-label assignment. The extractio

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Zhang, Jiaqing, Mingxiang Cao, Xue Yang, Kai Jiang, and Yunsong Li. "DiffCLIP: Few-shot Language-driven Multimodal Classifier." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 21 (2025): 22443–51. https://doi.org/10.1609/aaai.v39i21.34401.

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Visual language models like Contrastive Language-Image Pretraining (CLIP) have shown impressive performance in analyzing natural images with language information. However, these models often encounter challenges when applied to specialized domains such as remote sensing due to the limited availability of image-text pairs for training. To tackle this issue, we introduce DiffCLIP, a novel framework that extends CLIP to effectively convey comprehensive language-driven semantic information for accurate classification of high-dimensional multimodal remote sensing images. DiffCLIP is a few-shot lear

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Zhou, Jian-Peng, Lei Chen, Tianyun Wang, and Min Liu. "iATC-FRAKEL: a simple multi-label web server for recognizing anatomical therapeutic chemical classes of drugs with their fingerprints only." Bioinformatics 36, no. 11 (2020): 3568–69. http://dx.doi.org/10.1093/bioinformatics/btaa166.

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Abstract Motivation Anatomical therapeutic chemical (ATC) classification system is very important for drug utilization and studies. Correct prediction of the 14 classes in the first level for given drugs is an essential problem for the study on such system. Several multi-label classifiers have been proposed in this regard. However, only two of them provided the web servers and their performance was not very high. On the other hand, although some rest classifiers can provide better performance, they were built based on some prior knowledge on drugs, such as information of chemical–chemical inte

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Li, Xiaomin, Mykhailo Sakevych, Gentry Atkinson, and Vangelis Metsis. "BioDiffusion: A Versatile Diffusion Model for Biomedical Signal Synthesis." Bioengineering 11, no. 4 (2024): 299. http://dx.doi.org/10.3390/bioengineering11040299.

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Machine learning tasks involving biomedical signals frequently grapple with issues such as limited data availability, imbalanced datasets, labeling complexities, and the interference of measurement noise. These challenges often hinder the optimal training of machine learning algorithms. Addressing these concerns, we introduce BioDiffusion, a diffusion-based probabilistic model optimized for the synthesis of multivariate biomedical signals. BioDiffusion demonstrates excellence in producing high-fidelity, non-stationary, multivariate signals for a range of tasks including unconditional, label-co

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Thomas, Jenkins, Goodwin Autumn, and Talafha Sameerah. "An ORSAC method for data cleaning inspired by RANSAC." International Journal of Informatics and Communication Technology 13, no. 3 (2024): 484–98. https://doi.org/10.11591/ijict.v13i3.pp484-498.

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In classification problems, mislabeled data can have a dramatic effect on the capability of a trained model. The traditional method of dealing with mislabeled data is through expert review. However, this is not always ideal, due to the large volume of data in many classification datasets, such as image datasets supporting deep learning models, and the limited availability of human experts for reviewing the data. Herein, we propose an ordered sample consensus (ORSAC) method to support data cleaning by flagging mislabeled data. This method is inspired by the random sample consensus (RANSAC) meth

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Wu, Xuan, Zhijie Zhang, Shengqing Xiong, et al. "A Near-Real-Time Flood Detection Method Based on Deep Learning and SAR Images." Remote Sensing 15, no. 8 (2023): 2046. http://dx.doi.org/10.3390/rs15082046.

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Owning to the nature of flood events, near-real-time flood detection and mapping is essential for disaster prevention, relief, and mitigation. In recent years, the rapid advancement of deep learning has brought endless possibilities to the field of flood detection. However, deep learning relies heavily on training samples and the availability of high-quality flood datasets is rather limited. The present study collected 16 flood events in the Yangtze River Basin and divided them into three categories for different purpose: training, testing, and application. An efficient methodology of dataset-

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Ouassit, Youssef, Soufiane Ardchir, Mohammed Yassine El Ghoumari, and Mohamed Azouazi. "A Brief Survey on Weakly Supervised Semantic Segmentation." International Journal of Online and Biomedical Engineering (iJOE) 18, no. 10 (2022): 83–113. http://dx.doi.org/10.3991/ijoe.v18i10.31531.

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Semantic Segmentation is the process of assigning a label to every pixel in the image that share same semantic properties and stays a challenging task in computer vision. In recent years, and due to the large availability of training data the performance of semantic segmentation has been greatly improved by using deep learning techniques. A large number of novel methods have been proposed. However, in some crucial fields we can't assure sufficient data to learn a deep model and achieves high accuracy. This paper aims to provide a brief survey of research efforts on deep-learning-based semantic

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Coggan, Andrew R. "Use of stable isotopes to study carbohydrate and fat metabolism at the whole-body level." Proceedings of the Nutrition Society 58, no. 4 (1999): 953–61. http://dx.doi.org/10.1017/s0029665199001263.

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The present review discusses the advantages and limitations of using stable-isotope tracers to assess carbohydrate and fat metabolism at the whole-body level. One advantage of stable-(v. radioactive-) isotope tracers is the relative ease with which the location of a label within a molecule can be determined using selected-ion-monitoring GC-mass spectrometry (SIM-GC- MS). This technique minimizes potential problems due to label recycling, allows the use of multiple-labelled compounds simultaneously (e.g. to quantify glucose cycling), and perhaps most importantly, has led to the development of u

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Xu, Siyi, Jian Wang, and Qingbing Sang. "Semi-Supervised Method for Underwater Object Detection Algorithm Based on Improved YOLOv8." Applied Sciences 15, no. 3 (2025): 1065. https://doi.org/10.3390/app15031065.

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Deep learning-based object detection technology is rapidly developing, and underwater object detection, an important subcategory, plays a crucial role in various fields such as underwater structure repair and maintenance, as well as marine scientific research. Some of the major challenges in underwater object detection are the relatively limited availability of underwater image and video datasets and the high cost of acquiring high-quality, diverse training data. To address this, we propose a novel underwater object detection method, SUD-YOLO, based on the Mean Teacher semi-supervised learning

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Ai, Zeren, Hui Cao, Manqi Wang, and Kaiwen Yang. "Ship Ballast Water System Fault Diagnosis Method Based on Multi-Feature Fusion Graph Convolution." Journal of Physics: Conference Series 2755, no. 1 (2024): 012028. http://dx.doi.org/10.1088/1742-6596/2755/1/012028.

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Abstract To tackle the issues of limited fault data, inadequate information availability, and subpar fault diagnosis within the realm of ship ballast water system condition monitoring, this paper presents a novel fault diagnosis methodology known as the Probabilistic Similarity and Linear Similarity-based Graph Convolutional Neural Network (PCGCN) model. PCGCN initially converts the ship’s ballast water system dataset into two distinct graph structures: a probabilistic topology graph and a correlation topology graph. It delves into data similarity by employing T-SNE for probabilistic similarit

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Zayed, A. E., M. M. Bassiony, U. M. Youssef, et al. "Non MRI Guided Accelerated Intermittent Theta Burst Stimulation is Effective in Patients with Treatment Resistant Depression and Suicidality." European Psychiatry 67, S1 (2024): S702. http://dx.doi.org/10.1192/j.eurpsy.2024.1459.

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IntroductionThe U.S. Food & Drug Administration (FDA) has cleared SNT (Stanford Neuromodulation Therapy) for treatment of major depressive disorder (MDD) in adults who have failed to achieve improvement from at least two prior trials of antidepressants. SNT protocol requires both structural and functional connectivity MRIs which is limited by high cost and lack of availability, its use without neuronavigation is still considered an off label use and need more investigation.Objectives1-To investigate efficacy of SNT like accelerated off-label protocol without Neuronavigation in treating pat

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Lattmann, Evelyn, Andreja Jovic, Julie Kim, et al. "Abstract 4306: Label-free melanoma phenotype classification using AI-based morphological profiling." Cancer Research 84, no. 6_Supplement (2024): 4306. http://dx.doi.org/10.1158/1538-7445.am2024-4306.

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Abstract Melanoma plasticity and heterogeneity contribute to therapeutic resistance and mortality, and the ability of melanoma cells to switch from melanocytic to mesenchymal phenotypes results in increased invasion and metastasis. Investigating the role of these phenotypic states has been challenging due to limited marker availability for each cell state. High-parameter molecular methods such as RNAseq have produced more descriptive gene signatures of phenotypic states, but these methods are cell-destructive, labor-intensive, expensive, and can take days to weeks to obtain a readout. Differen

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Bernardo-Seisdedos, Ganeko, Jorge M. Charco, Itxaso SanJuan, et al. "Improving the Pharmacological Properties of Ciclopirox for Its Use in Congenital Erythropoietic Porphyria." Journal of Personalized Medicine 11, no. 6 (2021): 485. http://dx.doi.org/10.3390/jpm11060485.

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Congenital erythropoietic porphyria (CEP), also known as Günther’s disease, results from a deficient activity in the fourth enzyme, uroporphyrinogen III synthase (UROIIIS), of the heme pathway. Ciclopirox (CPX) is an off-label drug, topically prescribed as an antifungal. It has been recently shown that it also acts as a pharmacological chaperone in CEP, presenting a specific activity in deleterious mutations in UROIIIS. Despite CPX is active at subtoxic concentrations, acute gastrointestinal (GI) toxicity was found due to the precipitation in the stomach of the active compound and subsequent a

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Iancu, Bogdan, Valentin Soloviev, Luca Zelioli, and Johan Lilius. "ABOships—An Inshore and Offshore Maritime Vessel Detection Dataset with Precise Annotations." Remote Sensing 13, no. 5 (2021): 988. http://dx.doi.org/10.3390/rs13050988.

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Availability of domain-specific datasets is an essential problem in object detection. Datasets of inshore and offshore maritime vessels are no exception, with a limited number of studies addressing maritime vessel detection on such datasets. For that reason, we collected a dataset consisting of images of maritime vessels taking into account different factors: background variation, atmospheric conditions, illumination, visible proportion, occlusion and scale variation. Vessel instances (including nine types of vessels), seamarks and miscellaneous floaters were precisely annotated: we employed a

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Chamnanchanunt, Supat, and Ponlapat Rojnuckarin. "Direct oral anticoagulants and travel-related venous thromboembolism." Open Medicine 13, no. 1 (2018): 575–82. http://dx.doi.org/10.1515/med-2018-0085.

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AbstractTravel- related thromboembolism reflects the relationship between venous thromboembolism (VTE) and long-haul flights. Although this condition is rare, it may cause significant morbidity and mortality. Therefore, travelers should be evaluated for the risks for thrombosis. Travel physicians should employ a clinical risk score and select in vestigations, prophylaxis, and treatment that are appropriate for each individual. This review summarizes current VTE clinical risk scores and patient management from various reliable guidelines. We summarized 16 reliable publications for reviewing dat

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See, Aaron Raymond, and Welsey Daniel Advincula. "Creating Tactile Educational Materials for the Visually Impaired and Blind Students Using AI Cloud Computing." Applied Sciences 11, no. 16 (2021): 7552. http://dx.doi.org/10.3390/app11167552.

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There are 24.5 million visually impaired and blind (VIB) students who have limited access to educational materials due to cost or availability. Although advancement in technology is prevalent, providing individualized learning using technology remains a challenge without the proper tools or experience. The TacPic system was developed as an online platform to create tactile educational materials (TEM) based on the image inputs of users who do not have prior experience in tactile photo development or 3D printing. The TacPic system allows the users to simply upload images to a website and uses AI

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Sheng, Taoran, and Manfred Huber. "Reducing Label Dependency in Human Activity Recognition with Wearables: From Supervised Learning to Novel Weakly Self-Supervised Approaches." Sensors 25, no. 13 (2025): 4032. https://doi.org/10.3390/s25134032.

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Human activity recognition (HAR) using wearable sensors has advanced through various machine learning paradigms, each with inherent trade-offs between performance and labeling requirements. While fully supervised techniques achieve high accuracy, they demand extensive labeled datasets that are costly to obtain. Conversely, unsupervised methods eliminate labeling needs but often deliver suboptimal performance. This paper presents a comprehensive investigation across the supervision spectrum for wearable-based HAR, with particular focus on novel approaches that minimize labeling requirements whi

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Deng, Linlin, and Xina Lu. "Study on Small Sample Text Classification Based on Multi-Level Self-Attention and Multi-Feature Residual Fusion under Data Enhancement." Frontiers in Computing and Intelligent Systems 12, no. 1 (2025): 70–78. https://doi.org/10.54097/ee4gsk44.

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In commercial applications, while traditional models can achieve comparable performance to mainstream large language models, they generally necessitate extensive training data. This requirement presents a significant challenge when processing complex, lengthy Chinese texts and multi-label classification tasks with limited data availability. Furthermore, conventional data augmentation techniques frequently disrupt the original word order, thereby diminishing their efficacy for pre-trained language model applications. To overcome these limitations, we introduce the MacBERT-CNN-BiLSTM model, whic

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Ryazanov, Igor, Amanda T. Nylund, Debabrota Basu, Ida-Maja Hassellöv, and Alexander Schliep. "Deep Learning for Deep Waters: An Expert-in-the-Loop Machine Learning Framework for Marine Sciences." Journal of Marine Science and Engineering 9, no. 2 (2021): 169. http://dx.doi.org/10.3390/jmse9020169.

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Driven by the unprecedented availability of data, machine learning has become a pervasive and transformative technology across industry and science. Its importance to marine science has been codified as one goal of the UN Ocean Decade. While increasing amounts of, for example, acoustic marine data are collected for research and monitoring purposes, and machine learning methods can achieve automatic processing and analysis of acoustic data, they require large training datasets annotated or labelled by experts. Consequently, addressing the relative scarcity of labelled data is, besides increasin

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Manessis, Georgios, Maciej Frant, Katarzyna Podgórska, et al. "Label-Free Detection of African Swine Fever and Classical Swine Fever in the Point-of-Care Setting Using Photonic Integrated Circuits Integrated in a Microfluidic Device." Pathogens 13, no. 5 (2024): 415. http://dx.doi.org/10.3390/pathogens13050415.

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Swine viral diseases have the capacity to cause significant losses and affect the sector’s sustainability, a situation further exacerbated by the lack of antiviral drugs and the limited availability of effective vaccines. In this context, a novel point-of-care (POC) diagnostic device incorporating photonic integrated circuits (PICs), microfluidics and information, and communication technology into a single platform was developed for the field diagnosis of African swine fever (ASF) and classical swine fever (CSF). The device targets viral particles and has been validated using oral fluid and se

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Elsandra, Yesi, Yofina Mulyati, Tiara Turay, and Nova Mustiqa. "Preferensi Masyarakat Muslim Indonesia Terhadap Web Quality, E-Trust dan E- Purchase Intention Makanan Halal Online di Jepang." Jurnal Ekonomi dan Bisnis Dharma Andalas 25, no. 2 (2023): 642–52. http://dx.doi.org/10.47233/jebd.v25i2.1035.

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This research is motivated by the needs of the Muslim community in Ishikawa Prefecture, Japan, for halal products. Given the limited availability of halal product distribution centers in countries with minority Muslim populations, recourse to online shopping platforms has emerged as a prominent avenue. It is noteworthy that these halal centers are predominantly concentrated in major urban areas such as Tokyo, Kyoto, and Osaka. To acquire halal products, the Muslim community visits halal online stores and effectively makes product selections through these websites. The research aims to investig

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Zabala-Blanco, David, Ruber Hernández-García, and Ricardo J. Barrientos. "SoftVein-WELM: A Weighted Extreme Learning Machine Model for Soft Biometrics on Palm Vein Images." Electronics 12, no. 17 (2023): 3608. http://dx.doi.org/10.3390/electronics12173608.

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Contactless biometric technologies such as palm vein recognition have gained more relevance in the present and immediate future due to the COVID-19 pandemic. Since certain soft biometrics like gender and age can generate variations in the visualization of palm vein patterns, these soft traits can reduce the penetration rate on large-scale databases for mass individual recognition. Due to the limited availability of public databases, few works report on the existing approaches to gender and age classification through vein pattern images. Moreover, soft biometric classification commonly faces th

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Lefebvre, Donatien, Kevin Blanco-Valle, Jacques-Antoine Hennekinne, et al. "Multiplex Detection of 24 Staphylococcal Enterotoxins in Culture Supernatant Using Liquid Chromatography Coupled to High-Resolution Mass Spectrometry." Toxins 14, no. 4 (2022): 249. http://dx.doi.org/10.3390/toxins14040249.

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Staphylococcal food poisoning outbreaks are caused by the ingestion of food contaminated with staphylococcal enterotoxins (SEs). Among the 27 SEs described in the literature to date, only a few can be detected using immuno-enzymatic-based methods that are strongly dependent on the availability of antibodies. Liquid chromatography, coupled to high-resolution mass spectrometry (LC-HRMS), has, therefore, been put forward as a relevant complementary method, but only for the detection of a limited number of enterotoxins. In this work, LC-HRMS was developed for the detection and quantification of 24

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Tomanic, Dragana, Zorana Kovacevic, Dragica Stojanovic, et al. "Metronidazole in the prophylaxis and treatment of dogs and cats." Zbornik Matice srpske za prirodne nauke, no. 141 (2021): 95–105. http://dx.doi.org/10.2298/zmspn2141095t.

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Ever since their discovery, antimicrobials have helped in controlling and treating infections in both humans and animals. The control of infectious diseases is endangered by the rise of microorganisms that are resistant to this group of drugs. Limited availability of authorized veterinary drugs leads to prescription of human approved drugs. The aim of our study was to describe metronidazole use patterns and its accordance with scientific literature in Serbia. Results have shown that majority of prescriptions were written to dogs, while 27.1% prescriptions were for cats. Most common general con

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Moore, Finola E., Elaine G. Garcia, Riadh Lobbardi, et al. "Single-cell transcriptional analysis of normal, aberrant, and malignant hematopoiesis in zebrafish." Journal of Experimental Medicine 213, no. 6 (2016): 979–92. http://dx.doi.org/10.1084/jem.20152013.

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Hematopoiesis culminates in the production of functionally heterogeneous blood cell types. In zebrafish, the lack of cell surface antibodies has compelled researchers to use fluorescent transgenic reporter lines to label specific blood cell fractions. However, these approaches are limited by the availability of transgenic lines and fluorescent protein combinations that can be distinguished. Here, we have transcriptionally profiled single hematopoietic cells from zebrafish to define erythroid, myeloid, B, and T cell lineages. We also used our approach to identify hematopoietic stem and progenit

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Shino, Michael Y., Francisco Javier Ibarrondo, Jesse L. Clark, et al. "A Phase I/II Randomized Trial of Higher Dose mRNA-1273 Boosters in Lung Transplant Recipients." OBM Transplantation 08, no. 04 (2024): 1–11. http://dx.doi.org/10.21926/obm.transplant.2404227.

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Higher-dose mRNA booster vaccines have not been well studied for transplant recipients. This study evaluated the safety, reactogenicity and immunogenicity of higher dose mRNA-1273 booster vaccines among lung transplant recipients (LTRs). This phase 1/2 open-label randomized clinical trial of higher-dose mRNA-1273 booster vaccination enrolled nineteen adult LTRs into the 50 ug (n=8) vs. 100 ug (n=11) groups before enrollment was terminated due to the availability of the bivalent mRNA-1273.222 vaccine. Local and systemic reactogenicity was predominantly mild or moderate in severity for both dose

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