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Journal articles on the topic 'Level 1 Features'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Krishna, Prasad. K., and Aithal Sreeramana. "Literature Review on Fingerprint Level 1 and Level 2 Features Enhancement to Improve Quality of Image." International Journal of Management, Technology, and Social Sciences (IJMTS) 2, no. 2 (2017): 8–19. https://doi.org/10.5281/zenodo.835608.

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Biometrics is the one most popular property in human distinguishing proof based on physical or behavioral features. The different physiological characteristics are Fingerprint, DNA, Face, hand, retina, ear features, and odor, where as behavioral characteristics or features are typing rhythm, gait, gesture, and voice with the basic premise that all are unique and all human beings are identified by these intrinsic traits. In the physiological traits, Fingerprint is most commonly utilized the biometric feature in diverse fields for identification and verification purpose. Fingerprint features can

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P., S. Aithal, and Prasad K. Krishna. "Fingerprint Image Segmentation: A Review of State of the Art Techniques." International Journal of Management, Technology, and Social Sciences (IJMTS) 2, no. 2 (2017): 28–39. https://doi.org/10.5281/zenodo.848191.

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In Automatic Fingerprint Identification System (AFIS), pre-processing of the image is a crucial process in deciding the quality and performance of the system. Pre-processing is consists many stages as Segmentation, Enhancement, Binarisation, and Thinning. In this segmentation is one of the steps of pre-processing which differentiate foreground and background region of fingerprint images. Segmentation is the separation of the fingerprint region or extraction of the presence of ridges from the background of the initial image. Segmentation is necessary because it constructs the region of interest

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Liu, Eryun, and Kai Cao. "Minutiae Extraction From Level 1 Features of Fingerprint." IEEE Transactions on Information Forensics and Security 11, no. 9 (2016): 1893–902. http://dx.doi.org/10.1109/tifs.2016.2541345.

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Alshdadi, Abdulrahman A., Rubab Mehboob, Hassan Dawood, Madini O. Alassafi, Rayed Alghamdi, and Hussain Dawood. "Exploiting Level 1 and Level 3 features of fingerprints for liveness detection." Biomedical Signal Processing and Control 61 (August 2020): 102039. http://dx.doi.org/10.1016/j.bspc.2020.102039.

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Cappelli, Raffaele, and Matteo Ferrara. "A fingerprint retrieval system based on level-1 and level-2 features." Expert Systems with Applications 39, no. 12 (2012): 10465–78. http://dx.doi.org/10.1016/j.eswa.2012.02.064.

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Fernando, Basura, Elisa Fromont, and Tinne Tuytelaars. "Mining Mid-level Features for Image Classification." International Journal of Computer Vision 108, no. 3 (2014): 186–203. http://dx.doi.org/10.1007/s11263-014-0700-1.

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Wang, Dingyi, and Haishun Du. "Multi-level Salient Feature Mining Network for Person Re-identification." Journal of Physics: Conference Series 2640, no. 1 (2023): 012001. http://dx.doi.org/10.1088/1742-6596/2640/1/012001.

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Abstract Person re-identification (Re-ID) algorithms can retrieve the same pedestrian’s images from an image gallery captured by multiple cameras when given a pedestrian image. Due to changes in pedestrian postures, illuminations, and perspectives, it remains a significant challenge to improve the accuracy of person re-identification. Although the attention mechanism can alleviate some of these issues, it causes attention-based methods to pay excessive attention to features in the most salient areas of images while ignoring discriminant features outside the most salient areas, resulting in the

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Wu, Shaojun, and Ling Gao. "Multi-Level Joint Feature Learning for Person Re-Identification." Algorithms 13, no. 5 (2020): 111. http://dx.doi.org/10.3390/a13050111.

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In person re-identification, extracting image features is an important step when retrieving pedestrian images. Most of the current methods only extract global features or local features of pedestrian images. Some inconspicuous details are easily ignored when learning image features, which is not efficient or robust to for scenarios with large differences. In this paper, we propose a Multi-level Feature Fusion model that combines both global features and local features of images through deep learning networks to generate more discriminative pedestrian descriptors. Specifically, we extract local

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Mei Serin Sitio, Claudia, Yuliant Sibaroni, and Sri Suryani Prasetiyowati. "IDENTIFYING POSSIBLE RUMOR SPREADERS ON TWITTER USING THE SVM AND FEATURE LEVEL EXTRACTION." Jurnal Teknik Informatika (Jutif) 4, no. 3 (2023): 611–18. http://dx.doi.org/10.52436/1.jutif.2023.4.3.868.

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In everyday life, many events occur and give rise to various kinds of information, which are also rumors. Rumors can cause fear and influence public opinion about the event in question. Identifying possible rumor spreaders is extremely helpful in preventing the spread of rumors. Feature extraction can be done to expand the feature set, which consists of conversational features in the form of social networks formed from user replies, user features such as following, tweet count, verified, etc., and tweet features with text analysis such as punctuation and sentiment values. These features become

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Сергей Алексеевич, Воронцов. "ON SOME FEATURES OF ANTI-CORRUPTION AT THE REGIONAL LEVEL." NORTH CAUCASUS LEGAL VESTNIK 1, no. 1 (2020): 130–34. http://dx.doi.org/10.22394/2074-7306-2020-1-1-130-134.

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Faisal, Assist prof Dr Moayad Mahdi, and Assist prof Dr Ahmed Heyal Jihad. "Style features in Chalk Door Novel." ALUSTATH JOURNAL FOR HUMAN AND SOCIAL SCIENCES, no. 226(1) (October 11, 2018): 1–14. http://dx.doi.org/10.36473/ujhss.v0i226(1).183.

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This research examines a distinctive narrative text (the chalk door) of a prominent writer at the level of Iraqi and Arab culture, writer (Ahmed Saadawi). This research examines that novel in the light of the stylistic linguistic approach, which relies on the linguistic structure of the literary text to study it, no doubt That fiction is one of the most appropriate literary genres for stylistic study, for the richness of the narrative text in different linguistic compositions and methods. The study included the three stylistic levels of study: morphological level, grammar level, and semantic l

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Zheng, Chunjun, Chunli Wang, and Ning Jia. "An Ensemble Model for Multi-Level Speech Emotion Recognition." Applied Sciences 10, no. 1 (2019): 205. http://dx.doi.org/10.3390/app10010205.

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Speech emotion recognition is a challenging and widely examined research topic in the field of speech processing. The accuracy of existing models in speech emotion recognition tasks is not high, and the generalization ability is not strong. Since the feature set and model design of effective speech directly affect the accuracy of speech emotion recognition, research on features and models is important. Because emotional expression is often correlated with the global features, local features, and model design of speech, it is often difficult to find a universal solution for effective speech emo

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Sorokina, Anna. "FEATURES OF STRATEGIC PLANNING AT THE MUNICIPAL LEVEL." Scientific Papers Collection of the Angarsk State Technical University 2024, no. 1 (2024): 483–86. http://dx.doi.org/10.36629/2686-7788-2024-1-483-486.

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The article examines the legislative framework for strategic planning at the municipal level. The features of municipal strategic planning are identified and characterized. Examples of strategic planning practice in the Angarsk municipality are given

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Bemmerl, Thomas, Franz Huber, and Robert Stampfl. "Features, design and implementation of high-level language debuggers." Microprocessors and Microsystems 12, no. 6 (1988): 331–40. http://dx.doi.org/10.1016/0141-9331(88)90190-1.

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Dubrovskyi, E. I., and B. V. Donskoi. "DYNAMICS AND FEATURES OF THE HUMORAL RESPONSE TO COVID-19." Likarska sprava, no. 1-2 (May 25, 2021): 3–8. http://dx.doi.org/10.31640/jvd.1-2.2021(1).

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Introduction. This publication describes the continuation of a research to determine the level of specific antibodies in patients in the long term after being suffered from COVID-19. Materials and methods. For this phase of the research, a group of patients who relapsed into a COVID-19 eight months ago (240 days) was examined. The group consists of 42 people. All patients, with no exception, had positive PCR results on COVID-19. Some patients were treated in Hospital № 4 in the infectious department, the other part was treated on an outpatient basis. All patients were relatively divided into t

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Poonguzhali, N., and M. Ezhilarasan. "A novel approach on cluster-based indexing technique for level-1 and level-2 fingerprint features." International Journal of Computational Intelligence Studies 3, no. 4 (2014): 320. http://dx.doi.org/10.1504/ijcistudies.2014.067033.

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Gao, Y. B., J. T. Gao, R. Ma, and L. D. Yang. "Research on user granularity-level personalized social text generation technology." Journal of Physics: Conference Series 2294, no. 1 (2022): 012015. http://dx.doi.org/10.1088/1742-6596/2294/1/012015.

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Abstract With the introduction of large-scale pre-trained language models, breakthroughs have been made in text generation technology research. On this basis, in order to assist users to complete personalized creation, this paper proposes a user-level fine-grained control generation model. First, we design the Encoder-Decoder framework based on the GPT2 structure, and model and encode the user’s static personalized information on the Encoder side. Then add a bidirectional independent attention module to receive the personalized feature vector on the Decoder side. The attention module in the or

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Kobenova, A. R., S. А. Faizullina, and M. A. Kanabekova. "Features of biological assets accounting." Bulletin of "Turan" University, no. 1 (March 28, 2022): 148–54. http://dx.doi.org/10.46914/1562-2959-2022-1-1-148-154.

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The scientific article discusses the peculiarities of accounting of the livestock industry at the present time, including biological assets. The Republic of Kazakhstan has a high potential in the field of agriculture, as it has appropriate natural and climatic conditions and rich pasture lands that contribute to the successful development of animal husbandry. Therefore, the peculiarities of accounting for agricultural production are that constant changes occur in the process of growing in the herd. The dynamics of livestock growth is indicated in special documents that can be defined as primar

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Zhang, Guangyu, and Lianqiang Niu. "Cross-modal multi-scale feature fusion-based RGB-T saliency object detection method." Journal of Physics: Conference Series 2562, no. 1 (2023): 012032. http://dx.doi.org/10.1088/1742-6596/2562/1/012032.

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Abstract To cope with the challenge of significant target detection in complex scenes, this study proposes an RGB-T significant target detection method called CMFF. The method utilizes the complete potential of RGB and thermal infrared modal images and employs a codec structure and cross-modal multiscale feature fusion techniques. In the coding stage, two VGG16 backbone networks are used for multi-level feature extraction and CBAM attention module feature enhancement, and the enhanced features are fused using a stepwise fusion approach. Meanwhile, the weights of the two modalities are assigned

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Liu, Pengcheng, and Jia Xiao. "An Evaluation Model of Level of Detail Consistency of Geographical Features on Digital Maps." ISPRS International Journal of Geo-Information 9, no. 6 (2020): 410. http://dx.doi.org/10.3390/ijgi9060410.

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This paper proposes a method to evaluate the level of detail (LoD) of geographic features on digital maps and assess their LoD consistency. First, the contour of the geometry of the geographic feature is sketched and the hierarchy of its graphical units is constructed. Using the quartile measurement method of statistical analysis, outliers of graphical units are eliminated and the average value of the graphical units below the bottom quartile is used as the statistical LoD parameter for a given data sample. By comparing the LoDs of homogeneous and heterogeneous features, we analyze the differe

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Wang, Zhihao, Yalan Liu, Yuhuan Ren, and Haojie Ma. "Object-Level Double Constrained Method for Land Cover Change Detection." Sensors 19, no. 1 (2018): 79. http://dx.doi.org/10.3390/s19010079.

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Land cover change detection based on remote sensing has become increasingly important for protecting the ecological environment. Spatial features of images can be extracted by object-level methods. However, the computational complexity is high when using many features to detect land cover change. Meanwhile, single-constrained change detection (SCCD) methods produce non-objective and inaccurate results. Therefore, we proposed a land cover change detection method: the object-level double constrained change detection (ODCD) method. First, spectral and spatial features were calculated based on mul

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Cosentino Lagomarsino, Marco, Alessandro L. Sellerio, Philip D. Heijning, and Bruno Bassetti. "Universal features in the genome-level evolution of protein domains." Genome Biology 10, no. 1 (2009): R12. http://dx.doi.org/10.1186/gb-2009-10-1-r12.

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Roller, Dieter. "Design by features: An approach to high level shape manipulations." Computers in Industry 12, no. 3 (1989): 185–91. http://dx.doi.org/10.1016/0166-3615(89)90065-1.

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Sorokina, O. A., N. I. Ivanov, L. E. Petrova, N. V. Komov, Yu A. Tsypkin, and A. V. Dontsov. "Main features of farm land management at the municipal level." IOP Conference Series: Earth and Environmental Science 579 (November 5, 2020): 012137. http://dx.doi.org/10.1088/1755-1315/579/1/012137.

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Andreev, Sergey. "Relationship of Multi-Level Features in the Armenian Text." Izvestia of Smolensk State University, no. 1(69) (May 23, 2025): 13–22. https://doi.org/10.35785/2072-9464-2025-69-1-13-22.

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This work pertains to the direction in philology, which sets the task of studying the features of description in works of art of a given locus and creating an image of a place in them. As a result of the analysis of such works, it is supposed to identify the main features that form the model of a given locus, and to identify their relationships. This article examines the relationship of a number of formal and semantic features included in the model of the Armenian text, which is realized in Russian poetry. As formal characteristics, the main parts of speech are involved in the study, the relat

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Fangquan, Wu, Liu Yichi, and Li Xiong. "Customer Power Demand Pattern Recognition and Feature Extraction under Multi-Level Fuzzy Evaluation Model." Journal of Physics: Conference Series 2979, no. 1 (2025): 012004. https://doi.org/10.1088/1742-6596/2979/1/012004.

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Abstract A challenging problem is to solve the low recall rate problem in customer electricity demand pattern recognition, as well as accurately identify customer electricity demand patterns and extract relevant features for power system planning, energy scheduling, and user demand prediction. This article proposes a method for pattern recognition and feature extraction of customer electricity demand through a multi-level fuzzy evaluation model. By collecting and preprocessing a large amount of customer electricity demand data, this paper establishes a multi-level fuzzy evaluation model for di

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Chaouiya, Claudine, Sarah M. Keating, Duncan Berenguier, et al. "SBML Level 3 package: Qualitative Models, Version 1, Release 1." Journal of Integrative Bioinformatics 12, no. 2 (2015): 691–730. http://dx.doi.org/10.1515/jib-2015-270.

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Summary Quantitative methods for modelling biological networks require an in-depth knowledge of the biochemical reactions and their stoichiometric and kinetic parameters. In many practical cases, this knowledge is missing. This has led to the development of several qualitative modelling methods using information such as, for example, gene expression data coming from functional genomic experiments. The SBML Level 3 Version 1 Core specification does not provide a mechanism for explicitly encoding qualitative models, but it does provide a mechanism for SBML packages to extend the Core specificati

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Sun, Guanxiong, Yang Hua, Guosheng Hu, and Neil Robertson. "MAMBA: Multi-level Aggregation via Memory Bank for Video Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 3 (2021): 2620–27. http://dx.doi.org/10.1609/aaai.v35i3.16365.

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State-of-the-art video object detection methods maintain a memory structure, either a sliding window or a memory queue, to enhance the current frame using attention mechanisms. However, we argue that these memory structures are not efficient or sufficient because of two implied operations: (1) concatenating all features in memory for enhancement, leading to a heavy computational cost; (2) frame-wise memory updating, preventing the memory from capturing more temporal information. In this paper, we propose a multi-level aggregation architecture via memory bank called MAMBA. Specifically, our mem

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Shi, Cuiping, Xinlei Zhang, Jingwei Sun, and Liguo Wang. "Remote Sensing Scene Image Classification Based on Dense Fusion of Multi-level Features." Remote Sensing 13, no. 21 (2021): 4379. http://dx.doi.org/10.3390/rs13214379.

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For remote sensing scene image classification, many convolution neural networks improve the classification accuracy at the cost of the time and space complexity of the models. This leads to a slow running speed for the model and cannot realize a trade-off between the model accuracy and the model running speed. As the network deepens, it is difficult to extract the key features with a sample double branched structure, and it also leads to the loss of shallow features, which is unfavorable to the classification of remote sensing scene images. To solve this problem, we propose a dual branch multi

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Lopes, Fernando, Vincent Courtillot, and Jean-Louis Le Mouël. "Triskeles and Symmetries of Mean Global Sea-Level Pressure." Atmosphere 13, no. 9 (2022): 1354. http://dx.doi.org/10.3390/atmos13091354.

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The evolution of mean sea-level atmospheric pressure since 1850 is analyzed using iterative singular spectrum analysis. Maps of the main components (the trends) reveal striking symmetries of order 3 and 4. The Northern Hemisphere (NH) displays a set of three positive features, forming an almost perfect equilateral triangle. The Southern Hemisphere (SH) displays a set of three positive features arranged as an isosceles triangle, with a possible fourth (weaker) feature. This geometry can be modeled as the Taylor–Couette flow of mode 3 (NH) or 4 (SH). The remarkable regularity and three-order sym

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LIN, LIN, and MEI-LING SHYU. "EFFECTIVE AND EFFICIENT VIDEO HIGH-LEVEL SEMANTIC RETRIEVAL USING ASSOCIATIONS AND CORRELATIONS." International Journal of Semantic Computing 03, no. 04 (2009): 421–44. http://dx.doi.org/10.1142/s1793351x09000860.

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Two important approaches in multimedia information retrieval are classification and the ranking of the retrieved results. The technique of performing classification using Association Rule Mining (ARM) has been utilized to detect the high-level features from the video, taking advantages of its high efficiency and accuracy. Motivated by the fact that the users are only interested in the top-ranked relevant results, ranking strategies have been adopted to sort the retrieved results. In this paper, an effective and efficient video high-level semantic retrieval framework that utilizes associations

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Xin, Chenjing, Xinfu Li, and Yunfeng Yuan. "Multilevel Features-Guided Network for Few-Shot Segmentation." Electronics 11, no. 19 (2022): 3195. http://dx.doi.org/10.3390/electronics11193195.

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The purpose of few-shot semantic segmentation is to segment unseen classes with only a few labeled samples. However, most methods ignore the guidance of low-level features for segmentation, leading to unsatisfactory results. Therefore, we propose a multilevel features-guided network using convolutional neural network techniques, which fully utilizes features from each level. It includes two novel designs: (1) a similarity-guided feature reinforcement module (SRM), which uses features from different levels, it enables sufficient guidance from the support set to the query set, thus avoiding the

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Nikolenko, Liudmyla. "PRINCIPLES OF POLICE ACTIVITY: ESSENCE AND FEATURES." Ukrainian polyceistics: theory, legislation, practice 1, no. 1 (2021): 19–25. http://dx.doi.org/10.32366/2709-9261-2021-1-1-19-25.

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This article is devoted to the study of the principles of the police of Ukraine. The principles of police activity defined in the Law of Ukraine "On the National Police" are considered and analyzed, namely: the rule of law, respect for human rights and freedoms, legality, political neutrality, interaction with the population on the basis of partnership, continuity. It is noted that since Ukraine has announced a course for integration into the European Community and approximation of the Ukrainian legal system to European and world standards, the introduction of Ukrainian legislation and princip

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Chen, Zengzheng, Jianxin Wang, and Yeru Wang. "Enhancing Food Image Recognition by Multi-Level Fusion and the Attention Mechanism." Foods 14, no. 3 (2025): 461. https://doi.org/10.3390/foods14030461.

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As a pivotal area of research in the field of computer vision, the technology for food identification has become indispensable across diverse domains including dietary nutrition monitoring, intelligent service provision in restaurants, and ensuring quality control within the food industry. However, recognizing food images falls within the domain of Fine-Grained Visual Classification (FGVC), which presents challenges such as inter-class similarity, intra-class variability, and the complexity of capturing intricate local features. Researchers have primarily focused on deep information in deep co

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Bihl, Trevor J., and Kenneth W. Bauer Jr. "Statistical Analysis of High-Level Features from State of the Union Addresses." International Journal of Information Systems and Social Change 8, no. 2 (2017): 50–73. http://dx.doi.org/10.4018/ijissc.2017040103.

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A computational political science approach is taken to analyze the State of the Union Addresses (SUA) from 1790 to 2015. While low-level features, e.g. linguistic characteristics, are commonly used for lexical analysis, the authors herein illustrate the utility of high-level features, e.g. Flesch-Kincaid readability, for knowledge discovery and discrimination between types of speeches. A process is developed and employed to exploit high-level features which employs 1) statistical clustering (k-means) and a literature review to define types of speeches (e.g. written or oral), 2) classification

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Pratama, A., and R. I. Media. "A rule-based approach with multi-level feature taxonomy for recognition of machining features from 3D solid models." Journal of Physics: Conference Series 1450 (February 2020): 012128. http://dx.doi.org/10.1088/1742-6596/1450/1/012128.

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Arini, DD, KN Ramadhani, and F. Sthevanie. "Detection of face spoofing using low-level features and shape analysis." Journal of Physics: Conference Series 1192 (March 2019): 012002. http://dx.doi.org/10.1088/1742-6596/1192/1/012002.

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PETRYSHYN, Nataliia, and Tetiana YAREMCHUK. "Features of application of knowledge management to ensure competitiveness of the enterprise." Economics. Finances. Law, no. 10/1 (October 29, 2021): 5–8. http://dx.doi.org/10.37634/efp.2021.10(1).1.

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Introduction. Today, in the era of intellectualization of the economy, knowledge is one of the most important assets and factors that forms the value of the organization. In this case, the main thing is not the creation of knowledge, but its productive use. Today, no one doubts that the future of a company depends on its ability to manage knowledge. Therefore, domestic enterprises (both private and public) need to implement a knowledge management system, learn to effectively manage knowledge and use it productively. The purpose of the paper is to study the main problems of knowledge management

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Filippova, Olga V. "Criminological Features of Regional Recidivism." Russian investigator 1 (January 12, 2023): 51–56. http://dx.doi.org/10.18572/1812-3783-2023-1-51-56.

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In this study, based on the analysis of statistical data on crime in Russia and federal districts, the features of recidivism in different regions are revealed. Differences are shown in the level and structure of recidivism, in the proportion and composition of persons who have previously committed crimes. The highest number of relapses is registered in the Volga, Central and Siberian federal districts. The highest recidivism rate per 100,000 people is observed in the Far Eastern Federal District. High intensity of recidivism is observed in those regions where an increased level of general cri

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Kawamoto, Noboru, Eisaku Ozawa, and Kazuhiko Suehiro. "Quantization of gl(1, R) Generalized Chern–Simons Theory in 1+1 Dimensions." Modern Physics Letters A 12, no. 04 (1997): 219–31. http://dx.doi.org/10.1142/s0217732397000224.

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We present a quantization of previously proposed generalized Chern–Simons theory with gl(1, R) algebra in 1+1 dimensions. This simplest model shares the common features of generalized CS theories: on-shell reducibility and violations of regularity. On-shell reducibility of the theory requires us to use the Lagrangian Batalin–Vilkovisky and/or Hamiltonian Batalin–Fradkin–Vilkovisky formulation. Since the regularity condition is violated, their quantization is not straightforward. In the present case we can show that both formulations give an equivalent result. It leads to an interpretation that

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Oi, Yuta, Ichita Taniyama, Haruki Minamoto, et al. "10093- MNG-4 PREDICTION MODEL FOR TUMOR GROWTH BY QUANTITATIVE IMAGE ANALYSIS FOR INCIDENTALLY DISCOVERED MENINGIOMAS." Neuro-Oncology Advances 6, Supplement_4 (2024): iv23. http://dx.doi.org/10.1093/noajnl/vdae173.090.

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Abstract PURPOSE Most factors identified in prior studies on meningioma enlargement are qualitative, with limited quantitative evaluation. Predicting future tumor growth from initial imaging of incidentally discovered meningiomas could inform treatment decisions. This study quantitatively evaluates imaging data at diagnosis to identify characteristics associated with tumor enlargement. METHODS We compared MRI T2 features from the initial imaging of 10 patients in a clearly enlarged group with 10 in a non-enlarged group. Using 3D Slicer and Slicer Radiomics plug-ins, we created a program to set

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Romanenkova, Elizaveta, Irina Eremina, Lubov Zilberman, et al. "Features of Slowly Progressive Type 1 Diabetes Mellitus in Overweight Adolescents." Journal of the Endocrine Society 5, Supplement_1 (2021): A658—A659. http://dx.doi.org/10.1210/jendso/bvab048.1343.

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Abstract Background: he obesity epidemic has led to an increase in the incidence of type 1 diabetes mellitus (T1DM) on the background of overweight. The combination of T1DM and obesity can lead to an erroneous diagnosis of type 2 diabetes (T2DM). Methods: The study included 35 adolescents with T1DM. Inclusion criteria were obesity at onset, high titer of diabetes-associated autoantibodies, and insulin requirement less than 0.5 U/kg with a diabetes duration of more than 6 months. We assessed the level of HbA1c, fasting level of insulin and c-peptide, and level during the Mixed-Meal Tolerance Te

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Pugin, E. V., and A. L. Zhiznyakov. "CLASSIFICATION OF FEATURES OF IMAGE SEQUENCES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-5/W6 (May 18, 2015): 79–81. http://dx.doi.org/10.5194/isprsarchives-xl-5-w6-79-2015.

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Processing of image sequences is a very actual trend now. This is confirmed with a vast amount of researches in that area. The possibility of an image sequence processing and pattern recognition became available because of increased computer capabilities and better photo and video cameras. The feature extraction is one of the main steps during image processing and pattern recognition. This paper presents a novel classification of features of image sequences. The proposed classification has three groups: 1) features of a single image, 2) features of an image sequence, 3) semantic features of an

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Listia, Refta, and Agus Harjoko. "Klasifikasi Massa pada Citra Mammogram Berdasarkan Gray Level Cooccurence Matrix (GLCM)." IJCCS (Indonesian Journal of Computing and Cybernetics Systems) 8, no. 1 (2014): 59. http://dx.doi.org/10.22146/ijccs.3496.

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AbstrakKanker payudara adalah penyakit yang paling umum dideritaoleh wanitapadabanyak negara. Pemeriksaan kanker payudara dapat dilakukan dengan menggunakan mamografi.Padapenelitianini, pendekatan yang diusulkan bertujuanuntuk mengklasifikasi mammogram berdasarkan tiga kelas yaitukelas normal, tumor jinak, dan tumor ganas. Sistem yang diusulkan terdiri dari empat langkah utamayaitu preprosesing, segmentasi, ekstraksi fitur dan klasifikasi. Padatahappreprosesingakandilakukangrayscale, interpolasi, amoeba mean filter dan segmentasi. Ekstraksi ciri menggunakan Gray Level Cooccurence Matrix (GLCM)

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Corredor, Germán, Jon Whitney, Viviana Arias, Anant Madabhushi, and Eduardo Romero. "Training a cell-level classifier for detecting basal-cell carcinoma by combining human visual attention maps with low-level handcrafted features." Journal of Medical Imaging 4, no. 2 (2017): 021105. http://dx.doi.org/10.1117/1.jmi.4.2.021105.

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Sudharani, K., Dr T. C. Sarma, and Dr K. Satya Prasad. "Brain Tumor Detection Using Texture Characterisation and Classification Based on the Grey-Level Co-Occurrence Matrix." International Journal of Electrical and Electronics Research 4, no. 2 (2016): 57–61. http://dx.doi.org/10.37391/ijeer.040204.

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Detection of brain tumour is very important current scenario of the health care society. Image processing techniques are used to extract the abnormal tumour portion and other features in the brain. Brain tumor is an abnormal mass of lesson in which cells grow up and multiply uncontrollably, apparently unregulated by the mechanisms that control cells. Several techniques like Segmentation, morphological have been developed for detection of tumor in the brain. Texture is a critical feature of several image types and textural features have a lot of application in image processing, content-based im

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Granaturov, V. M., and I. A. Korablinova. "FEATURES AND CONSEQUENCES OF MANIFESTATION OF INFORMATION RISKS AT THE GLOBAL LEVEL IN MODERN CONDITIONS." Proceedings of the O.S. Popov ОNAT 1, no. 1 (2020): 108–19. http://dx.doi.org/10.33243/2518-7139-2020-1-1-108-119.

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The article is devoted to the risk analysis associated with the use of information and information technologies. Activation and deployment of “digital transformation programs” are accompanied by the emergence of new or unfamiliar challenges and threats; they have a significant negative impact on all aspects of society and are called as “information risks”. It has been shown that any modern entity with social and economic relations provides a wide range of information risks. The purpose of the research is to identify and substantiate the existing problems of qualitative analysis of the emergenc

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Popova, Irina, and Nataliya Demchenko. "TERRITORIAL SOCIETIES FEATURES: EUROPEAN EXPERIENCE." Three Seas Economic Journal 1, no. 1 (2020): 20–27. http://dx.doi.org/10.30525/2661-5150/2020-1-4.

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The purpose of the article is to summarize the experience of developing tools for the implementation of amalgamated territorial communities. The European countries’ experience helps to improve the system of public administration in such a way that it acts in the interests of the individual-citizen and is under the control of civil society. The important factors in the dynamic development of the state is effective public administration at all levels of the administrative and territorial structure of the country are investigated. The main links in this section are the district and regional level

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Li, Xudong, Yan Zhang, Yunhang Shen, et al. "Feature Denoising Diffusion Model for Blind Image Quality Assessment." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 5 (2025): 5004–12. https://doi.org/10.1609/aaai.v39i5.32530.

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Blind Image Quality Assessment (BIQA) aims to evaluate image quality in line with human perception, without reference benchmarks. Currently, deep learning BIQA methods typically depend on using features from high-level tasks for transfer learning. However, the inherent differences between BIQA and these high-level tasks inevitably introduce noise into the quality-aware features. In this paper, we take an initial step toward exploring the diffusion model for feature denoising in BIQA, namely Perceptual Feature Diffusion for IQA (PFD-IQA), which aims to remove noise from quality-aware features.

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Satria Mandala and Yusril Ramadhan. "ANALYSIS FEATURE EXTRACTION FOR OPTIMIZING ARRHYTHMIA CLASSIFICATION FROM ELECTROCARDIOGRAM SIGNALS." Jurnal Teknik Informatika (Jutif) 5, no. 1 (2024): 97–104. https://doi.org/10.52436/1.jutif.2024.5.1.1267.

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Heart disease is the primary cause of death globally, with arrhythmias, such as Premature Atrial Contraction (PAC), Atrial Fibrillation (AF), and Premature Ventricular Contraction (PVC), being critical heart rhythm abnormalities. Although numerous studies have utilized feature extraction from electrocardiogram (ECG) signals to detect these conditions, optimal accuracy has not been achieved. Therefore, this research aims to identify relevant features and achieve better results by using dynamic feature extraction methods. The extracted features used are RR Interval, PR Interval, and QRS Complex.

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