Results 21 to 30 of about 1,645,295 (287)
A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects [PDF]
IEEE Transactions on Neural Networks and Learning Systems, 2020 A convolutional neural network (CNN) is one of the most significant networks in the deep learning field. Since CNN made impressive achievements in many areas, including but not limited to computer vision and natural language processing, it attracted much
Zewen Li +4 more
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Computational and topological properties of neural networks by means of graph-theoretic parameters
Alexandria Engineering Journal, 2023 A neural network is a computer system modeled on the nerve tissue and nervous system. In this sense, neural networks refer to systems of neurons, either organic or artificial in nature.
Asad Khan +5 more
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An overview of neural networks for medical image recognition [PDF]
E3S Web of Conferences, 2023 Medical image recognition plays a crucial role in computer diagnostics and has been greatly enhanced by the advancements in deep learning techniques, particularly neural networks.
Berezovsky V.V., Vygovskaya N.V.
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V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation [PDF]
International Conference on 3D Vision, 2016 Convolutional Neural Networks (CNNs) have been recently employed to solve problems from both the computer vision and medical image analysis fields. Despite their popularity, most approaches are only able to process 2D images while most medical data used ...
F. Milletarì +2 more
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Journal of Imaging, 2023 Artificial neural networks can solve various tasks in computer vision, such as image classification, object detection, and general recognition.
Ladislav Karrach, Elena Pivarčiová
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AI-Track-tive: open-source software for automated recognition and counting of surface semi-tracks using computer vision (artificial intelligence) [PDF]
Geochronology, 2021 A new method for automatic counting of etched fission tracks in minerals is described and presented in this article. Artificial intelligence techniques such as deep neural networks and computer vision were trained to detect fission surface semi-tracks on
S. Nachtergaele, J. De Grave
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ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2019 Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs).
Qilong Wang +5 more
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Quantum Neural Network for Quantum Neural Computing
Research, 2023 Neural networks have achieved impressive breakthroughs in both industry and academia. How to effectively develop neural networks on quantum computing devices is a challenging open problem. Here, we propose a new quantum neural network model for quantum neural computing using (classically controlled) single-qubit operations and measurements on real ...
Min-Gang Zhou +5 more
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Neural computing with coherent laser networks
Nanophotonics, 2023 AbstractWe show that coherent laser networks (CLNs) exhibit emergent neural computing capabilities. The proposed scheme is built on harnessing the collective behavior of laser networks for storing a number of phase patterns as stable fixed points of the governing dynamical equations and retrieving such patterns through proper excitation conditions ...
Mohammad-Ali Miri, Vinod Menon
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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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