Results 31 to 40 of about 1,645,295 (287)
Physics-informed neural networks (PINNs) for fluid mechanics: a review [PDF]
Acta Mechanica Sinica, 2021 Despite the significant progress over the last 50 years in simulating flow problems using numerical discretization of the Navier–Stokes equations (NSE), we still cannot incorporate seamlessly noisy data into existing algorithms, mesh-generation is ...
Shengze Cai +4 more
semanticscholar +1 more source
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
doaj +1 more source
Non-local Neural Networks [PDF]
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2017 Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family of building blocks for capturing long-range dependencies.
X. Wang +3 more
semanticscholar +1 more source
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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DeepFool: A Simple and Accurate Method to Fool Deep Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2015 State-of-the-art deep neural networks have achieved impressive results on many image classification tasks. However, these same architectures have been shown to be unstable to small, well sought, perturbations of the images. Despite the importance of this
Seyed-Mohsen Moosavi-Dezfooli +2 more
semanticscholar +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Artificial Neural Networks for Microwave Computer-Aided Design: The State of the Art
IEEE transactions on microwave theory and techniques, 2022 This article presents an overview of artificial neural network (ANN) techniques for a microwave computer-aided design (CAD). ANN-based techniques are becoming useful for performing forward/inverse modeling for active/passive components to enhance a ...
F. Feng +5 more
semanticscholar +1 more source
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
doaj +1 more source