Results 21 to 30 of about 6,721,355 (335)
Few‐shot learning with relation propagation and constraint
IET Computer Vision, 2021 Previous deep learning methods usually required large‐scale annotated data, which is computationally exhaustive and unrealistic in certain scenarios. Therefore, few‐shot learning, where only a few annotated training images are available for training, has
Huiyun Gong +6 more
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Output sensitive algorithms for covering many points [PDF]
Discrete Mathematics & Theoretical Computer Science, 2015 Discrete ...
Hossein Ghasemalizadeh +1 more
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VarSight: prioritizing clinically reported variants with binary classification algorithms
BMC Bioinformatics, 2019 Background When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient’s phenotypes. Typically, this is done through annotation, filtering, and then prioritization of
James M. Holt +15 more
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Coordination in software development [PDF]
Communications of the ACM, 1995 Since its inception, the software industry has been in crisis. As Blazer noted 20 years ago, “[Software] is unreliable, delivered late, unresponsive to change, inefficient, and expensive … and has been for the past 20 years” [4]. In a survey of software contractors and government contract officers, over half of the respondents believed that calendar ...
Kraut, Robert E., Streeter, Lynn A.
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An Efficient Density-Based Local Outlier Detection Approach for Scattered Data
IEEE Access, 2019 After the local outlier factor was first proposed, there is a large family of local outlier detection approaches derived from it. Since the existing approaches only focus on the extent of overall separation between an object and its neighbors, and ignore
Shubin Su +6 more
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Multitask learning for biomedical named entity recognition with cross-sharing structure
BMC Bioinformatics, 2019 Background Biomedical named entity recognition (BioNER) is a fundamental and essential task for biomedical literature mining, which affects the performance of downstream tasks.
Xi Wang, Jiagao Lyu, Li Dong, Ke Xu
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Multiple Level Hierarchical Network-Based Clause Selection for Emotion Cause Extraction
IEEE Access, 2019 Emotion cause extraction is one of the most important applications in natural language processing tasks. It is a difficult challenge due to the complex semantic information between emotion description and the whole document.
Xinyi Yu +4 more
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Random Blur Data Augmentation for Scene Text Recognition
IEEE Access, 2021 In this paper, we propose to apply data augmentation approaches that provide more diverse training images, thus helping train more robust deep models for the Scene Text Recognition (STR) task.
Deguo Mu, Wei Sun, Guoliang Xu, Wei Li
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Development and software piracy
Economics, 2018 Abstract In this paper, the authors analyze the differences in piracy rates from one country to another. Like previous papers on the topic, they find that more developed countries have lower incentives for pirating. Unlike previous papers, they find that the piracy rate is positively correlated with the tax burden rate but negatively ...
Martínez-Sánchez, Francisco +1 more
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ReqGen: Keywords-Driven Software Requirements Generation
Mathematics, 2023 Software requirements specification is undoubtedly critical for the whole software life-cycle. Currently, writing software requirements specifications primarily depends on human work.
Ziyan Zhao +5 more
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