Results 11 to 20 of about 31,169 (266)
CoRR, 2014 Sequence prediction and classification are ubiquitous and challenging problems in machine learning that can require identifying complex dependencies between temporally distant inputs. Recurrent Neural Networks (RNNs) have the ability, in theory, to cope with these temporal dependencies by virtue of the short-term memory implemented by their recurrent ...
Jan Koutník +3 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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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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Improved Recurrent Neural Network based BP Decoding Algorithm for Polar Codes
Guangtongxin yanjiu, 2022 In recent years, the emerging Deep Learning (DL) technology has made progress in the field of decoding. Current polar code neural network decoder has faster convergence speed and better Bit Error Rate (BER) performance than Belief Propagation (BP ...
Xue-lu DENG, Da-qin PENG
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Successive Image Generation from a Single Sentence [PDF]
ITM Web of Conferences, 2021 Through various examples in history such as the early man’s carving on caves, dependence on diagrammatic representations, the immense popularity of comic books we have seen that vision has a higher reach in communication than written words. In this paper,
Parab Amogh +4 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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JOIV: International Journal on Informatics Visualization, 2021 Distributed-Denial-of-Service impacts are undeniably significant, and because of the development of IoT devices, they are expected to continue to rise in the future.
Abdulkareem A. Hezam +4 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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RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks
Advances in Neural Information Processing Systems 35, 2022 Published as a conference paper at NeurIPS ...
Leo Kozachkov +2 more
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