Gotowe bibliografie tematyczne / Model annotation

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Gotowa bibliografia na temat „Model annotation”

Autor: Grafiati
Data publikacji: 31 sierpnia 2024
Data aktualizacji: 31 lipca 2025

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Artykuły w czasopismach na temat "Model annotation"

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Benitez-Garcia, Gibran, Jesus Olivares-Mercado, Gabriel Sanchez-Perez, and Hiroki Takahashi. "IPN HandS: Efficient Annotation Tool and Dataset for Skeleton-Based Hand Gesture Recognition." Applied Sciences 15, no. 11 (2025): 6321. https://doi.org/10.3390/app15116321.

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Hand gesture recognition (HGR) heavily relies on high-quality annotated datasets. However, annotating hand landmarks in video sequences is a time-intensive challenge. In this work, we introduce IPN HandS, an enhanced version of our IPN Hand dataset, which now includes approximately 700,000 hand skeleton annotations and corrected gesture boundaries. To generate these annotations efficiently, we propose a novel annotation tool that combines automatic detection, inter-frame interpolation, copy–paste capabilities, and manual refinement. This tool significantly reduces annotation time from 70 min t
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Liu, Zheng. "LDA-Based Automatic Image Annotation Model." Advanced Materials Research 108-111 (May 2010): 88–94. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.88.

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This paper presents LDA-based automatic image annotation by visual topic learning and related annotation extending. We introduce the Latent Dirichlet Allocation (LDA) model in visual application domain. Firstly, the visual topic which is most relevant to the unlabeled image is obtained. According to this visual topic, the annotations with highest likelihood serve as seed annotations. Next, seed annotations are extended by analyzing the relationship between seed annotations and related Flickr tags. Finally, we combine seed annotations and extended annotations to construct final annotation set.
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Okpala, Ebuka, and Long Cheng. "Large Language Model Annotation Bias in Hate Speech Detection." Proceedings of the International AAAI Conference on Web and Social Media 19 (June 7, 2025): 1389–418. https://doi.org/10.1609/icwsm.v19i1.35879.

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Large language models (LLMs) are fast becoming ubiquitous and have shown impressive performance in various natural language processing (NLP) tasks. Annotating data for downstream applications is a resource-intensive task in NLP. Recently, the use of LLMs as a cost-effective data annotator for annotating data used to train other models or as an assistive tool has been explored. Yet, little is known regarding the societal implications of using LLMs for data annotation. In this work, focusing on hate speech detection, we investigate how using LLMs such as GPT-4 and Llama-3 for hate speech detecti
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Paun, Silviu, Bob Carpenter, Jon Chamberlain, Dirk Hovy, Udo Kruschwitz, and Massimo Poesio. "Comparing Bayesian Models of Annotation." Transactions of the Association for Computational Linguistics 6 (December 2018): 571–85. http://dx.doi.org/10.1162/tacl_a_00040.

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The analysis of crowdsourced annotations in natural language processing is concerned with identifying (1) gold standard labels, (2) annotator accuracies and biases, and (3) item difficulties and error patterns. Traditionally, majority voting was used for 1, and coefficients of agreement for 2 and 3. Lately, model-based analysis of corpus annotations have proven better at all three tasks. But there has been relatively little work comparing them on the same datasets. This paper aims to fill this gap by analyzing six models of annotation, covering different approaches to annotator ability, item d
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Misirli, Goksel, Matteo Cavaliere, William Waites, et al. "Annotation of rule-based models with formal semantics to enable creation, analysis, reuse and visualization." Bioinformatics 32, no. 6 (2015): 908–17. http://dx.doi.org/10.1093/bioinformatics/btv660.

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Abstract Motivation: Biological systems are complex and challenging to model and therefore model reuse is highly desirable. To promote model reuse, models should include both information about the specifics of simulations and the underlying biology in the form of metadata. The availability of computationally tractable metadata is especially important for the effective automated interpretation and processing of models. Metadata are typically represented as machine-readable annotations which enhance programmatic access to information about models. Rule-based languages have emerged as a modelling
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Li, Huadong, Ying Wei, Han Peng, and Wei Zhang. "DiffuPrompter: Pixel-Level Automatic Annotation for High-Resolution Remote Sensing Images with Foundation Models." Remote Sensing 16, no. 11 (2024): 2004. http://dx.doi.org/10.3390/rs16112004.

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Instance segmentation is pivotal in remote sensing image (RSI) analysis, aiding in many downstream tasks. However, annotating images with pixel-wise annotations is time-consuming and laborious. Despite some progress in automatic annotation, the performance of existing methods still needs improvement due to the high precision requirements for pixel-level annotation and the complexity of RSIs. With the support of large-scale data, some foundational models have made significant progress in semantic understanding and generalization capabilities. In this paper, we delve deep into the potential of t
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Chu, Zhendong, Jing Ma, and Hongning Wang. "Learning from Crowds by Modeling Common Confusions." Proceedings of the AAAI Conference on Artificial Intelligence 35, no. 7 (2021): 5832–40. http://dx.doi.org/10.1609/aaai.v35i7.16730.

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Crowdsourcing provides a practical way to obtain large amounts of labeled data at a low cost. However, the annotation quality of annotators varies considerably, which imposes new challenges in learning a high-quality model from the crowdsourced annotations. In this work, we provide a new perspective to decompose annotation noise into common noise and individual noise and differentiate the source of confusion based on instance difficulty and annotator expertise on a per-instance-annotator basis. We realize this new crowdsourcing model by an end-to-end learning solution with two types of noise a
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Rotman, Guy, and Roi Reichart. "Multi-task Active Learning for Pre-trained Transformer-based Models." Transactions of the Association for Computational Linguistics 10 (2022): 1209–28. http://dx.doi.org/10.1162/tacl_a_00515.

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Abstract Multi-task learning, in which several tasks are jointly learned by a single model, allows NLP models to share information from multiple annotations and may facilitate better predictions when the tasks are inter-related. This technique, however, requires annotating the same text with multiple annotation schemes, which may be costly and laborious. Active learning (AL) has been demonstrated to optimize annotation processes by iteratively selecting unlabeled examples whose annotation is most valuable for the NLP model. Yet, multi-task active learning (MT-AL) has not been applied to state-
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Wen-Yi, Andrea W., Kathryn Adamson, Nathalie Greenfield, et al. "Automate or Assist? The Role of Computational Models in Identifying Gendered Discourse in US Capital Trial Transcripts." Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7 (October 16, 2024): 1556–66. http://dx.doi.org/10.1609/aies.v7i1.31746.

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The language used by US courtroom actors in criminal trials has long been studied for biases. However, systematic studies for bias in high-stakes court trials have been difficult, due to the nuanced nature of bias and the legal expertise required. Large language models offer the possibility to automate annotation. But validating the computational approach requires both an understanding of how automated methods fit in existing annotation workflows and what they really offer. We present a case study of adding a computational model to a complex and high-stakes problem: identifying gender-biased l
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Luo, Yan, Tianxiu Lu, Weihan Zhang, Suiqun Li, and Xuefeng Wang. "Augmenting Three-Dimensional Model Annotation System with Enhanced Reality." Journal of Computing and Electronic Information Management 12, no. 2 (2024): 1–7. http://dx.doi.org/10.54097/uv15ws76.

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This study proposes an augmented reality-based three-dimensional model annotation system, integrating cloud anchors, three-dimensional reconstruction, and augmented reality technology to achieve explicit three-dimensional annotations on models. Employing an improved ORB algorithm, the annotated model is persistently anchored in three-dimensional space through cloud anchors, presenting accurate spatial information and showcasing the depth of scenes and relationships between elements. The system supports multiple data types for annotations, such as text and images. Through a comparison with trad
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Rozprawy doktorskie na temat "Model annotation"

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Hu, Rong (RongRong). "Image annotation with discriminative model and annotation refinement by visual similarity matching." Thesis, Massachusetts Institute of Technology, 2009. http://hdl.handle.net/1721.1/61311.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 65-67).<br>A large percentage of photos on the Internet cannot be reached by search engines because of the absence of textual metadata. Such metadata come from description and tags of the photos by their uploaders. Despite of decades of research, neither model based and model-free approaches can provide quality annotation to images. In this thesis, I present a hybrid annotation pipeline that comb
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Balachandar, Shreerekha. "Back annotation for conceptual structures." Thesis, This resource online, 1995. http://scholar.lib.vt.edu/theses/available/etd-06112009-063732/.

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Elias, Mturi. "Design of Business Process Model Repositories : Requirements, Semantic Annotation Model and Relationship Meta-model." Doctoral thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-117035.

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Business process management is fast becoming one of the most important approaches for designing contemporary organizations and information systems. A critical component of business process management is business process modelling. It is widely accepted that modelling of business processes from scratch is a complex, time-consuming and error-prone task. However the efforts made to model these processes are seldom reused beyond their original purpose. Reuse of business process models has the potential to overcome the challenges of modelling business processes from scratch. Process model repositor
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Jones, Martin Robert. "Deep metabolome annotation of the freshwater model species, Daphnia magna." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7984/.

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In the 21st century - the era of big data science - chemical risk assessment procedures remain woefully dependent upon a suite of basic toxicological assays that offer little, if any, biochemical information pertaining to the underlying mechanism of toxicity. Metabolomics, defined as the holistic study of all naturally occurring, low molecular weight metabolites present within a biological system, holds huge potential as a tool to fill this knowledge gap, and thereby, to revolutionise the chemical risk assessment process through provision of rich molecular information . Owing to on-going chall
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Khalili, Ali. "A Semantics-based User Interface Model for Content Annotation, Authoring and Exploration." Doctoral thesis, Universitätsbibliothek Leipzig, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-159956.

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The Semantic Web and Linked Data movements with the aim of creating, publishing and interconnecting machine readable information have gained traction in the last years. However, the majority of information still is contained in and exchanged using unstructured documents, such as Web pages, text documents, images and videos. This can also not be expected to change, since text, images and videos are the natural way in which humans interact with information. Semantic structuring of content on the other hand provides a wide range of advantages compared to unstructured information. Semantically-enr
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Banks, Russell K. "Annotation Tools for Multivariate Gene Set Testing of Non-Model Organisms." DigitalCommons@USU, 2015. https://digitalcommons.usu.edu/etd/4515.

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Many researchers across a wide range of disciplines have turned to gene expression anal- ysis to aid in predicting and understanding biological outcomes and mechanisms. Because genes are known to work in a dependent manner, it’s common for researchers to first group genes in biologically meaningful sets and then test each gene set for differential expression. Comparisons are made across different treatment/condition groups. The meta-analytic method for testing differential activity of gene sets, termed multi-variate gene set testing (mvGST), will be used to provide context for two persistent a
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Harmon, Trev R. "On-Line Electronic Document Collaboration and Annotation." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1589.pdf.

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Basu, Roy Sreeya. "Automated Annotation of Simulink Generated C Code Based on the Simulink Model." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-284564.

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There has been a wave of transformation in the automotive industry in recent years, with most vehicular functions being controlled electron- ically instead of mechanically. This has led to an exponential increase in the complexity of software functions in vehicles, making it essential for manufactures to guarantee their correctness. Traditional software testing is reaching its limits, consequently pushing the automotive in- dustry to explore other forms of quality assurance. One such technique that has been gaining momentum over the years is a set of verification techniques based on mathematic
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Dorribo, Camba Jorge. "ANNOTATION MECHANISMS TO MANAGE DESIGN KNOWLEDGE IN COMPLEX PARAMETRIC MODELS AND THEIR EFFECTS ON ALTERATION AND REUSABILITY." Doctoral thesis, Universitat Politècnica de València, 2015. http://hdl.handle.net/10251/45997.

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El proyecto de investigación propuesto se enmarca dentro del área de diseño de producto con aplicaciones de modelado sólido CAD/CAM (Computer Aided Design/Computer Aided Manufacturing). Concretamente, se pretende hacer un estudio de las herramientas de anotación asociativas disponibles en las aplicaciones comerciales de modelado CAD con el fin de analizar su uso, viabilidad, eficiencia y efectos en la modificación y reutilización de modelos digitales 3D, así como en la gestión y comunicación del conocimiento técnico vinculado al diseño. La idea principal de esta investigación doctoral es est
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Li, Honglin. "Hierarchical video semantic annotation the vision and techniques /." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1071863899.

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Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xv, 146 p.; also includes graphics. Includes bibliographical references (p. 136-146).
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Książki na temat "Model annotation"

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Oliver J. Bear Don't Walk. Inferring Race and Ethnicity from Clinical Notes: Annotation, Model Auditing, and Ethical Implications. [publisher not identified], 2022.

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Wallace, Don. Model foreign investment law: With annotations. International Law Institute, 1996.

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F, Del Duca Louis, and American Bar Association. Section of Urban, State, and Local Government Law., eds. Annotations to the Model procurement code for state and local governments, with analytical summary of state enactments. 3rd ed. Section of State and Local Government Law, American Bar Association, 1996.

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Padó, Sebastian. Cross-lingual annotation projection models for role-semantic information. Saarland University, 2007.

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American Bar Association. Section of Business Law, ed. Model business corporation act annotated: Model business corporation act with official comments and reporter's annotations. 2nd ed. Section of Business Law, American Bar Association, 2013.

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American Bar Association. Committee on Corporate Laws. Model business corporation act annotated: Model business corporation act with official comment and reporter's annotations : model close corporation supplement : model professional corporation supplement. The Section, 2008.

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American Bar Association. Committee on Corporate Laws. and American Bar Foundation, eds. Model Business Corporation Act annotated: Model Business Corporation Act with official comment and reporter's annotations : Model Close Corporation supplement, Model Professional Corporation supplement. 3rd ed. Section of Business Law, American Bar Association, 1998.

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J, Falvey Patrick, Adler Theodore A, and American Bar Association. Section of Urban, State, and Local Government Law., eds. Annotations to the Model procurement code for state and local governments. Section of Urban, State, and Local Government Law, American Bar Association, 1987.

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Brants, Thorsten. Tagging and parsing with cascaded Markov models: Automation of corpus annotation. DFKI, 1999.

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Ronnberg, Erik A. R. Pilot schooner Hesper of Boston, 1884: Plans with annotations and descriptive keys. E.A.R. Ronnberg, Jr., 1994.

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Części książek na temat "Model annotation"

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Pustejovsky, James, Harry Bunt, and Annie Zaenen. "Designing Annotation Schemes: From Theory to Model." In Handbook of Linguistic Annotation. Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-0881-2_2.

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Ide, Nancy, Christian Chiarcos, Manfred Stede, and Steve Cassidy. "Designing Annotation Schemes: From Model to Representation." In Handbook of Linguistic Annotation. Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-0881-2_3.

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Kralj Novak, Petra, Teresa Scantamburlo, Andraž Pelicon, Matteo Cinelli, Igor Mozetič, and Fabiana Zollo. "Handling Disagreement in Hate Speech Modelling." In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08974-9_54.

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AbstractHate speech annotation for training machine learning models is an inherently ambiguous and subjective task. In this paper, we adopt a perspectivist approach to data annotation, model training and evaluation for hate speech classification. We first focus on the annotation process and argue that it drastically influences the final data quality. We then present three large hate speech datasets that incorporate annotator disagreement and use them to train and evaluate machine learning models. As the main point, we propose to evaluate machine learning models through the lens of disagreement
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Zhao, Yong, Michael Wilde, and Ian Foster. "Applying the Virtual Data Provenance Model." In Provenance and Annotation of Data. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890850_16.

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Buneman, Peter, Adriane Chapman, James Cheney, and Stijn Vansummeren. "A Provenance Model for Manually Curated Data." In Provenance and Annotation of Data. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890850_17.

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Mannai, Zayneb, Anis Kalboussi, and Ahmed Hadj Kacem. "An Approach for Modeling Annotation in the e-Health Domain." In Digital Health Transformation, Smart Ageing, and Managing Disability. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43950-6_24.

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AbstractIn our research, we established a medical annotation model in the form of an ontology in an effort to ensure data interchange amongst medical annotation systems. We employ the “patient partner” approach to involve the patient in the medical annotative activity. In fact, the patient will be able to register, annotate, and comprehend the comments made in his medical file utilizing this new paradigm.
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Cohen, K. Bretonnel, Karin Verspoor, Karën Fort, et al. "The Colorado Richly Annotated Full Text (CRAFT) Corpus: Multi-Model Annotation in the Biomedical Domain." In Handbook of Linguistic Annotation. Springer Netherlands, 2017. http://dx.doi.org/10.1007/978-94-024-0881-2_53.

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Aldinucci, Marco, Sonia Campa, Peter Kilpatrick, Fabio Tordini, and Massimo Torquati. "An Abstract Annotation Model for Skeletons." In Formal Methods for Components and Objects. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35887-6_14.

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Bowers, Shawn, Timothy McPhillips, Bertram Ludäscher, Shirley Cohen, and Susan B. Davidson. "A Model for User-Oriented Data Provenance in Pipelined Scientific Workflows." In Provenance and Annotation of Data. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11890850_15.

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Leung, Man-Kit, Thomas Mandl, Edward A. Lee, et al. "Scalable Semantic Annotation Using Lattice-Based Ontologies." In Model Driven Engineering Languages and Systems. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04425-0_31.

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Streszczenia konferencji na temat "Model annotation"

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Ji, Tianhao, Dazi Li, Xin Ma, and Dong Gao. "Knowledge Extraction Model Based on Semi-automatic Annotation." In 2024 8th International Symposium on Computer Science and Intelligent Control (ISCSIC). IEEE, 2024. https://doi.org/10.1109/iscsic64297.2024.00045.

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Huang, Chen, Yang Deng, Wenqiang Lei, Jiancheng Lv, and Ido Dagan. "Selective Annotation via Data Allocation: These Data Should Be Triaged to Experts for Annotation Rather Than the Model." In Findings of the Association for Computational Linguistics: EMNLP 2024. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-emnlp.17.

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Dorribo-Camba, Jorge, Gerardo Alducin-Quintero, Pascual Perona, and Manuel Contero. "Enhancing Model Reuse Through 3D Annotations: A Theoretical Proposal for an Annotation-Centered Design Intent and Design Rationale Communication." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-64595.

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The long term goals of this research are to study the effectiveness of CAD 3D annotation techniques to support the explicit communication of design intent and rationale, and to analyze the impact of the annotations in the alteration and reutilization of 3D models in a product design context. Towards these goals, we are initially examining the formal annotation practices defined by model-based standards such as ASME Y14.41-2012 and ISO 16792:2006, and their implementation in current CAD systems. This paper presents a prototype implementation of a module to automatically extract textual informat
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Bao, Zhenshan, Yuezhang Wang, and Wenbo Zhang. "Low-Resource Named Entity Recognition without Human Annotation." In 2nd International Conference on Machine Learning Techniques and NLP (MLNLP 2021). Academy and Industry Research Collaboration Center (AIRCC), 2021. http://dx.doi.org/10.5121/csit.2021.111427.

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Most existing approaches to named entity recognition (NER) rely on a large amount of highquality annotations or a more complete specific entity lists. However, in practice, it is very expensive to obtain manually annotated data, and the list of entities that can be used is often not comprehensive. Using the entity list to automatically annotate data is a common annotation method, but the automatically annotated data is usually not perfect under low-resource conditions, including incomplete annotation data or non-annotated data. In this paper, we propose a NER system for complex data processing
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Chen, Zhijun, Huimin Wang, Hailong Sun, et al. "Structured Probabilistic End-to-End Learning from Crowds." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/210.

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End-to-end learning from crowds has recently been introduced as an EM-free approach to training deep neural networks directly from noisy crowdsourced annotations. It models the relationship between true labels and annotations with a specific type of neural layer, termed as the crowd layer, which can be trained using pure backpropagation. Parameters of the crowd layer, however, can hardly be interpreted as annotator reliability, as compared with the more principled probabilistic approach. The lack of probabilistic interpretation further prevents extensions of the approach to account for importa
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Zhang, Dabin, Meng Chen, Weiming Huang, Yongshun Gong, and Kai Zhao. "Exploring Urban Semantics: A Multimodal Model for POI Semantic Annotation with Street View Images and Place Names." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/280.

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Semantic annotation for points of interest (POIs) is the process of annotating a POI with a category label, which facilitates many services related to POIs, such as POI search and recommendation. Most of the existing solutions extract features related to POIs from abundant user-generated content data (e.g., check-ins and user comments). However, such data are often difficult to obtain, especially for newly created POIs. In this paper, we aim to explore semantic annotation for POIs with limited information such as POI (place) names and geographic locations. Additionally, we have found that the
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Cheng, Zehua, and Lianlong Wu. "Hybrid Learning System for Large-scale Medical Image Analysis." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/824.

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Adequate annotated data cannot always be satisfied in medical imaging applications. To address such a challenge, we would explore ways to reduce the quality and quantity of annotations requirements of the deep learning model by developing a hybrid learning system. We combined self-supervised learning, semi-supervised learning and weak-supervised learning to improve annotation utilization. Our primary research work on 2D medical image detection under poor annotation conditions has found that better regularization and adversarial loss can improve the robustness and performance with poor annotati
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Chamberlain, Jon. "The annotation-validation (AV) model." In the First International Workshop. ACM Press, 2014. http://dx.doi.org/10.1145/2594776.2594779.

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Rahayu, Syarifah Bahiyah, Shahrul Azman Noah, and Andrianto Arfan Wardhana. "Semantic Document Annotation Ranking Model." In 2010 Second International Conference on Advances in Computing, Control and Telecommunication Technologies (ACT). IEEE, 2010. http://dx.doi.org/10.1109/act.2010.56.

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Hejabi, Parsa, Akshay Kiran Padte, Preni Golazizian, et al. "CVAT-BWV: A Web-Based Video Annotation Platform for Police Body-Worn Video." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/1006.

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We introduce an open-source platform for annotating body-worn video (BWV) footage aimed at enhancing transparency and accountability in policing. Despite the widespread adoption of BWVs in police departments, analyzing the vast amount of footage generated has presented significant challenges. This is primarily due to resource constraints, the sensitive nature of the data, which limits widespread access, and consequently, lack of annotations for training machine learning models. Our platform, called CVAT-BWV, offers a secure, locally hosted annotation environment that integrates several AI tool
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Raporty organizacyjne na temat "Model annotation"

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Mbani, Benson, Valentin Buck, and Jens Greinert. Megabenthic Fauna Detection with Faster R-CNN (FaunD-Fast) Short description of the research software. GEOMAR, 2023. http://dx.doi.org/10.3289/sw_1_2023.

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This is an A.I. - based workflow for detecting megabenthic fauna from a sequence of underwater optical images. The workflow (semi) automatically generates weak annotations through the analysis of superpixels, and uses these (refined and semantically labeled) annotations to train a Faster R-CNN model. Currently, the workflow has been tested with images of the Clarion-Clipperton Zone in the Pacific Ocean
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Gur, Amit, Edward Buckler, Joseph Burger, Yaakov Tadmor, and Iftach Klapp. Characterization of genetic variation and yield heterosis in Cucumis melo. United States Department of Agriculture, 2016. http://dx.doi.org/10.32747/2016.7600047.bard.

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Project objectives: 1) Characterization of variation for yield heterosis in melon using Half-Diallele (HDA) design. 2) Development and implementation of image-based yield phenotyping in melon. 3) Characterization of genetic, epigenetic and transcriptional variation across 25 founder lines and selected hybrids. The epigentic part of this objective was modified during the course of the project: instead of characterization of chromatin structure in a single melon line through genome-wide mapping of nucleosomes using MNase-seq approach, we took advantage of rapid advancements in single-molecule se
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Or, Etti, David Galbraith, and Anne Fennell. Exploring mechanisms involved in grape bud dormancy: Large-scale analysis of expression reprogramming following controlled dormancy induction and dormancy release. United States Department of Agriculture, 2002. http://dx.doi.org/10.32747/2002.7587232.bard.

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The timing of dormancy induction and release is very important to the economic production of table grape. Advances in manipulation of dormancy induction and dormancy release are dependent on the establishment of a comprehensive understanding of biological mechanisms involved in bud dormancy. To gain insight into these mechanisms we initiated the research that had two main objectives: A. Analyzing the expression profiles of large subsets of genes, following controlled dormancy induction and dormancy release, and assessing the role of known metabolic pathways, known regulatory genes and novel se
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