Results 1 to 10 of about 333 (129)
Frontiers in Cell and Developmental Biology, 2021 DNA methylation is one of the most extensive epigenetic modifications. DNA 4mC modification plays a key role in regulating chromatin structure and gene expression.
Rao Zeng, Song Cheng, Minghong Liao
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MTL-FFDET: A Multi-Task Learning-Based Model for Forest Fire Detection
Forests, 2022 Deep learning-based forest fire vision monitoring methods have developed rapidly and are becoming mainstream. The existing methods, however, are based on enormous amounts of data, and have issues with weak feature extraction, poor small target recognition and many missed and false detections in complex forest scenes.
Jingwen Huang +2 more
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FSPMTL: Flexible Self-Paced Multi-Task Learning
IEEE Access, 2020 Multi-Task Learning (MTL) is a method to simultaneously utilize commonalities and differences across tasks to improve the learning performances with limited data.
Lijian Sun, Yun Zhou
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A 3D-CNN and LSTM Based Multi-Task Learning Architecture for Action Recognition
IEEE Access, 2019 Multi-task learning (MTL) is a machine learning method to share knowledge for multiple related machine learning tasks via learning those tasks jointly. It has been shown to be capable of effectively improving the generalization capability of each single ...
Xi Ouyang +6 more
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HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition
IEEE Transactions on Image Processing, 2017 In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep
Jianping Fan +2 more
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STG-MTL: scalable task grouping for multi-task learning using data maps
Machine Learning: Science and TechnologyMulti-Task Learning (MTL) is a powerful technique that has gained popularity due to its performance improvement over traditional Single-Task Learning (STL).
Ammar Sherif +3 more
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LogSE: An Uncertainty-Based Multi-Task Loss Function for Learning Two Regression Tasks [PDF]
Journal of Universal Computer Science, 2022 Multi-task learning (MTL) is a popular method in machine learning which utilizes related information of multi tasks to learn a task more efficiently and accurately.
Zeinab Ghasemi-Naraghi +2 more
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AST-MTL: An Attention-Based Multi-Task Learning Strategy for Traffic Forecasting [PDF]
IEEE Access, 2021 Road traffic forecasting is crucial in Intelligent Transportation Systems (ITS). To achieve accurate results, it is necessary to model the dynamic nature and the complex non-linear dependencies governing traffic. The goal is particularly challenging when the prediction involves more than just one traffic variable. This paper proposes a novel multi-task
Giovanni Buroni +2 more
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IEEE Access, 2023 Deep learning, particularly Convolutional Neural Networks, has demonstrated effectiveness in computer-aided diagnosis applications, including knee osteoarthritis analysis.
Pauline Shan Qing Yeoh +4 more
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ADMET property prediction via multi-task graph learning under adaptive auxiliary task selection
iScience, 2023 Summary: It is a critical step in lead optimization to evaluate the absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties of drug-like compounds.
Bing-Xue Du +4 more
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