Results 41 to 50 of about 324,009 (309)
ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks [PDF]
2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020 Recently, channel attention mechanism has demonstrated to offer great potential in improving the performance of deep convolutional neural networks (CNNs). However, most existing methods dedicate to developing more sophisticated attention modules for achieving better performance, which inevitably increase model complexity.
Qinghua Hu +5 more
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Efficient ear alignment using a two‐stack hourglass network
IET Biometrics, 2023 Ear images have been shown to be a reliable modality for biometric recognition with desirable characteristics, such as high universality, distinctiveness, measurability and permanence. While a considerable amount of research has been directed towards ear
Anja Hrovatič +3 more
doaj +1 more source
Neural waves and computation in a neural net model I: Convolutional hierarchies
Journal of Computational Neuroscience, 2023 Abstract The computational resources of a neuromorphic network model introduced earlier are investigated in the context of such hierarchical systems as the mammalian visual cortex. It is argued that a form of ubiquitous spontaneous local convolution, driven by spontaneously arising wave-like activity---which itself promotes local Hebbian ...
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PANDA: Pose Aligned Networks for Deep Attribute Modeling [PDF]
, 2014 We propose a method for inferring human attributes (such as gender, hair style, clothes style, expression, action) from images of people under large variation of viewpoint, pose, appearance, articulation and occlusion.
Bourdev, Lubomir +4 more
core +1 more source
Advanced Materials Interfaces, EarlyView., 2023 This review discusses the use of Surface‐Enhanced Raman Spectroscopy (SERS) combined with Artificial Intelligence (AI) for detecting antimicrobial resistance (AMR). Various SERS studies used with AI techniques, including machine learning and deep learning, are analyzed for their advantages and limitations.
Zakarya Al‐Shaebi +4 more
wiley +1 more source
SRI3D: Two‐stream inflated 3D ConvNet based on sparse regularization for action recognition
IET Image Processing, 2023 Although most state‐of‐the‐art action recognition models have adopted a two‐stream 3D convolutional structure as a backbone network, few works have studied the impact of loss functions on action recognition models.
Zhaoqilin Yang +4 more
doaj +1 more source
Butterfly-Net: Optimal Function Representation Based on Convolutional Neural Networks [PDF]
Communications in Computational Physics, 2020 Deep networks, especially convolutional neural networks (CNNs), have been successfully applied in various areas of machine learning as well as to challenging problems in other scientific and engineering fields. This paper introduces Butterfly-Net, a low-complexity CNN with structured and sparse cross-channel connections, together with a Butterfly ...
Li, Y, Cheng, X, Lu, J
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IET Intelligent Transport Systems, 2023 Rail transit has many advantages, such as large passenger capacity, convenience, safety, and environmental protection, making it the preferred travel mode for most passengers.
Xuanrong Zhang +3 more
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Convolutional neural net face recognition works in non-human-like ways [PDF]
Royal Society Open Science, 2020 Convolutional neural networks (CNNs) give the state-of-the-art performance in many pattern recognition problems but can be fooled by carefully crafted patterns of noise. We report that CNN face recognition systems also make surprising ‘errors'. We tested six commercial face recognition CNNs and found that they outperform typical human participants on ...
Peter J. B. Hancock +2 more
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Multi‐objective single‐shot neural architecture search via efficient convolutional filters
Electronics Letters, 2023 This paper presents a novel approach for fast neural architecture search (NAS) in Convolutional Neural Networks (CNNs) for end‐to‐end License Plate Recognition (LPR).
Seyed Mahdi Shariatzadeh +2 more
doaj +1 more source