Results 21 to 30 of about 52,085 (312)
SA-Net: Shuffle Attention for Deep Convolutional Neural Networks [PDF]
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021 Attention mechanisms, which enable a neural network to accurately focus on all the relevant elements of the input, have become an essential component to improve the performance of deep neural networks. There are mainly two attention mechanisms widely used in computer vision studies, spatial attention and channel attention, which aim to capture the ...
Qing-Long Zhang, Yu-Bin Yang
openaire +3 more sources
Deep Net Tree Structure for Balance of Capacity and Approximation Ability
Frontiers in Applied Mathematics and Statistics, 2019 Deep learning has been successfully used in various applications including image classification, natural language processing and game theory. The heart of deep learning is to adopt deep neural networks (deep nets for short) with certain structures to ...
Charles K. Chui +4 more
doaj +1 more source
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
doaj +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
Convolutional deep rectifier neural nets for phone recognition [PDF]
Interspeech 2013, 2013 Rectifier neurons differ from standard ones only in that the sigmoid activation function is replaced by the rectifier function, max(0, x). Several recent studies suggest that rectifier units may be more suitable building units for deep nets. For example, we found that with deep rectifier networks one can attain a similar speech recognition performance ...
László Tóth
openalex +2 more sources
Simplicial 2-Complex Convolutional Neural Nets
, 2020 Recently, neural network architectures have been developed to accommodate when the data has the structure of a graph or, more generally, a hypergraph. While useful, graph structures can be potentially limiting. Hypergraph structures in general do not account for higher order relations between their hyperedges. Simplicial complexes offer a middle ground,
Bunch, Eric +3 more
openaire +2 more sources
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
BA-Net: Bridge Attention for Deep Convolutional Neural Networks
, 2022 In recent years, channel attention mechanism has been widely investigated due to its great potential in improving the performance of deep convolutional neural networks (CNNs) in many vision tasks. However, in most of the existing methods, only the output of the adjacent convolution layer is fed into the attention layer for calculating the channel ...
Yue Zhao +3 more
openaire +2 more sources
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
Vehicle Re-identification method based on Swin-Transformer network
Array, 2022 Vehicle Re-identification is to find out the exact vehicle captured by other cameras given a vehicle image. In natural traffic surveillance systems, vehicle re-identification can play a role in target vehicles localization, supervision, and criminal ...
Jianrong Li +4 more
doaj +1 more source