Results 41 to 50 of about 418,704 (219)
Which Artificial Intelligence Algorithm Better Predicts the Chinese Stock Market?
IEEE Access, 2018 Unpredictable stock market factors make it difficult to predict stock index futures. Although efforts to develop an effective prediction method have a long history, recent developments in artificial intelligence and the use of artificial neural networks ...
Lin Chen +5 more
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Deep learning in Emergency Medicine: Recent contributions and methodological challenges
Emergency Care Journal, 2020 In the last few years, artificial intelligence (AI) technology has grown dramatically impacting several fields of human knowledge and medicine in particular.
Francesco Faita
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Exploiting more robust and efficacious deep learning techniques for modeling wind power with speed
Energy Reports, 2022 Sound analyses of the nonlinear relationship between wind speed and power generation are crucial for the advancement of wind energy optimization. As an emerging artificial intelligence technology, deep learning has received growing attention from energy ...
Hao Chen, Reidar Staupe-Delgado
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Learning Convolutional Text Representations for Visual Question Answering
, 2018 Visual question answering is a recently proposed artificial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically ...
Ji, Shuiwang, Wang, Zhengyang
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Artificial Neural Networks and Deep Learning for Genomic Prediction of Continuous Outcomes [PDF]
, 2022 AbstractThis chapter provides elements for implementing deep neural networks (deep learning) for continuous outcomes. We give details of the hyperparameters to be tuned in deep neural networks and provide a general guide for doing this task with more probability of success.
Osval Antonio Montesinos López +2 more
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Safe Mutations for Deep and Recurrent Neural Networks through Output Gradients
, 2018 While neuroevolution (evolving neural networks) has a successful track record across a variety of domains from reinforcement learning to artificial life, it is rarely applied to large, deep neural networks.
Chen, Jay +3 more
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Deep Learning and Its Applications in Biomedicine
Genomics, Proteomics & Bioinformatics, 2018 Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences.
Chensi Cao +8 more
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A Comprehensive Review of Deep Learning: Architectures, Recent Advances, and Applications
InformationDeep learning (DL) has become a core component of modern artificial intelligence (AI), driving significant advancements across diverse fields by facilitating the analysis of complex systems, from protein folding in biology to molecular discovery in ...
Ibomoiye Domor Mienye, Theo G. Swart
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Using Explainable AI to Measure Feature Contribution to Uncertainty
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 The application of artificial intelligence techniques in safety-critical domains such as medicine and self-driving vehicles has raised questions regarding its trustworthiness and reliability.
Katherine Elizabeth Brown +1 more
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Deep learning from crowds [PDF]
, 2017 Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the state-of-the-art in various domains. However, as the size of supervised artificial neural networks grows, typically so does the need for
Pereira, Francisco, Rodrigues, Filipe
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