Results 41 to 50 of about 3,683,270 (301)
Powerset Convolutional Neural Networks
CoRR, 2019 We present a novel class of convolutional neural networks (CNNs) for set functions, i.e., data indexed with the powerset of a finite set. The convolutions are derived as linear, shift-equivariant functions for various notions of shifts on set functions.
Wendler, Chris +2 more
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NeuroImage: Clinical, 2019 We hypothesized that expert epileptologists can detect seizures directly by visually analyzing EEG plot images, unlike automated methods that analyze spectro-temporal features or complex, non-stationary features of EEG signals.
Ali Emami +5 more
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Normalized Convolutional Neural Network
CoRR, 2020 We introduce a Normalized Convolutional Neural Layer, a novel approach to normalization in convolutional networks. Unlike conventional methods, this layer normalizes the rows of the im2col matrix during convolution, making it inherently adaptive to sliced inputs and better aligned with kernel structures. This distinctive approach differentiates it from
Dongsuk Kim +4 more
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Color Filter Array Demosaicking Using Densely Connected Residual Network
IEEE Access, 2019 Deep convolutional neural networks have been used extensively in recent image processing research, exhibiting drastically improved performance. In this study, we apply convolutional neural networks to color filter array demosaicking, which plays an ...
Bumjun Park, Jechang Jeong
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Quantum convolutional neural networks [PDF]
Nature Physics, 2019 12 pages, 11 figures. v2: New application to optimizing quantum error correction codes, added sample complexity analysis, more details for experimental realizations, and other minor ...
Iris Cong +2 more
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Data-Driven Bearing Fault Diagnosis for Induction Motor
Journal of Electrical and Computer Engineering, 2023 Bearings are critical components in modern manufacturing, yet they are prone to failures in induction machines. Detecting these faults early can reduce repair costs.
Aqib Raqeeb +5 more
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Sequential Convolutional Recurrent Neural Networks for Fast Automatic Modulation Classification
IEEE Access, 2021 A novel and efficient end-to-end learning model for automatic modulation classification is proposed for wireless spectrum monitoring applications, which automatically learns from the time domain in-phase and quadrature data without requiring the design ...
Kaisheng Liao +4 more
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Lazy training of radial basis neural networks [PDF]
, 2006 Proceeding of: 16th International Conference on Artificial Neural Networks, ICANN 2006. Athens, Greece, September 10-14, 2006Usually, training data are not evenly distributed in the input space.
Galván, Inés M. +5 more
core +1 more source
IEEE Access, 2020 To solve the problem of data sparsity in recommendation systems, this paper proposes a probabilistic matrix factorization recommendation of self-attention mechanism convolutional neural networks with item auxiliary information.
Chenkun Zhang, Cheng Wang
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Journal of Education, Health and Sport, 2021 Convolutional neural networks (CNNs) are used in many areas of computer vision, such as object tracking and recognition, security, military, and biomedical image analysis.
Szymon Płotka +4 more
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