Results 11 to 20 of about 30,985 (264)
AN OVERVIEW OF DEEP LEARNING TECHNIQUES FOR SHORT-TERM ELECTRICITY LOAD FORECASTING [PDF]
Applied Computer Science, 2019 This paper presents an overview of some Deep Learning (DL) techniques applicable to forecasting electricity consumptions, especially in the short-term horizon.
Saheed ADEWUYI +4 more
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Surgical phase recognition by learning phase transitions
Current Directions in Biomedical Engineering, 2020 Automatic recognition of surgical phases is an important component for developing an intra-operative context-aware system. Prior work in this area focuses on recognizing short-term tool usage patterns within surgical phases.
Sahu Manish +3 more
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Journal of Intelligent Systems, 2023 With the rapid growth of informatics systems’ technology in this modern age, the Internet of Things (IoT) has become more valuable and vital to everyday life in many ways. IoT applications are now more popular than they used to be due to the availability
Aswad Firas Mohammed +4 more
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A noise reduction forecasting method of bus load based on sequence decomposition
Zhejiang dianli, 2023 In the context of new power systems， the diverse distributed power sources and user-side behavior have introduced instability in bus loads， thus presenting a fresh challenge for short-term load forecasting.
YANG Jian +5 more
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Efficient processing of GRU based on word embedding for text classification
JOIV: International Journal on Informatics Visualization, 2019 Text classification has become very serious problem for big organization to manage the large amount of online data and has been extensively applied in the tasks of Natural Language Processing (NLP).
Muhammad Zulqarnain +3 more
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Supply and Demand Forecasting Model of Multi-Agricultural Products Based on Deep Learning
智慧农业, 2022 To further improve the simulation and estimation accuracy of the supply and demand process of agricultural products, a large number of agricultural data at the national and provincial levels since 1980 were used as the basic research sample, including ...
ZHUANG Jiayu +5 more
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Lung Cancer Prognosis Through Standardized Pre-Processing And Multifaceted Data Enhancement: A Deep Learning Approach [PDF]
SHS Web of ConferencesWith high rates of morbidity and mortality, lung cancer continues to be a major problem for world health. A precise prognosis is essential for clinical judgment and patient care.
Nathan Revathy, Rithani M.
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Proceedings of the 34th ACM International Conference on Supercomputing, 2020 Recurrent neural networks (RNNs) have been widely adopted in temporal sequence analysis, where realtime performance is often in demand. However, RNNs suffer from heavy computational workload as the model often comes with large weight matrices. Pruning schemes have been proposed for RNNs to eliminate the redundant (close-to-zero) weight values.
Runbin Shi +8 more
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Explainability and Adversarial Robustness for RNNs [PDF]
2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService), 2020 Accepted at IEEE BigDataService ...
Alexander Hartl +3 more
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Heartbeat Sound Signal Classification Using Deep Learning
Sensors, 2019 Presently, most deaths are caused by heart disease. To overcome this situation, heartbeat sound analysis is a convenient way to diagnose heart disease. Heartbeat sound classification is still a challenging problem in heart sound segmentation and feature ...
Ali Raza +5 more
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