Results 11 to 20 of about 815,001 (281)
A New Method on Kerma Estimation in Mammography Screenings [PDF]
Journal of Biomedical Physics and Engineering, 2021 Background: Given the extensive use and preferred diagnostic method in common mammography tests for screening and diagnosis of breast cancer, there is concern about the increased dose absorbed by the patient due to the sensitivity of the breast tissue ...
Mohammad Nabipour +4 more
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An Interactive Visualization for Feature Localization in Deep Neural Networks
Frontiers in Artificial Intelligence, 2020 Deep artificial neural networks have become the go-to method for many machine learning tasks. In the field of computer vision, deep convolutional neural networks achieve state-of-the-art performance for tasks such as classification, object detection, or ...
Martin Zurowietz, Tim W. Nattkemper
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Review of dynamic gesture recognition
Virtual Reality & Intelligent Hardware, 2021 In recent years, gesture recognition has been widely used in the fields of intelligent driving, virtual reality, and human-computer interaction. With the development of artificial intelligence, deep learning has achieved remarkable success in computer ...
Yuanyuan SHI +4 more
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Artificial neural network approach for acute poisoning mortality prediction in emergency departments [PDF]
Clinical and Experimental Emergency Medicine, 2021 Objective The number of deaths due to acute poisoning (AP) is on the increase. It is crucial to predict AP patient mortality to identify those requiring intensive care for providing appropriate patient care as well as preserving medical resources.
Seon Yeong Park +6 more
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Transition between individually different and common features in skilled drumming movements
Frontiers in Sports and Active Living, 2022 Why do professional athletes and musicians exhibit individually different motion patterns? For example, baseball pitchers generate various pitching forms, e.g., variable wind-up, cocking, and follow-through forms.
Ken Takiyama +2 more
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Spiking neural networks for computer vision [PDF]
Interface Focus, 2018 State-of-the-art computer vision systems use frame-based cameras that sample the visual scene as a series of high-resolution images. These are then processed using convolutional neural networks using neurons with continuous outputs. Biological vision systems use a quite different approach, where the eyes (cameras) sample the visual scene continuously ...
Michael Hopkins +3 more
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DETECTION OF ATTACKS ON A COMPUTER NETWORK BASED ON THE USE OF NEURAL NETWORKS COMPLEX
Nauka ta progres transportu, 2020 Purpose. The article is aimed at the development of a methodology for detecting attacks on a computer network. To achieve this goal the following tasks were solved: to develop a methodology for detecting attacks on a computer network based on an ensemble
I. V. Zhukovyts'kyy +3 more
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Benchmarking Neural Networks For Quantum Computations [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2019 Revised substantially, and resubmitted to IEEE Transactions on Neural Networks and Learning ...
Nam H. Nguyen +3 more
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Measurement: Sensors, 2021 The convolutional neural network is a subfield of artificial neural networks and has made great achievements in various domains over the past decade.
Hengyi Li +5 more
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A Taxonomy of Deep Convolutional Neural Nets for Computer Vision [PDF]
, 2016 Traditional architectures for solving computer vision problems and the degree of success they enjoyed have been heavily reliant on hand-crafted features.
Babu, R. Venkatesh +5 more
core +2 more sources