DKD–DAD: a novel framework with discriminative kinematic descriptor and deep attention-pooled descriptor for action recognition
Sign Up to like & getrecommendations! Published in 2019 at "Neural Computing and Applications"
DOI: 10.1007/s00521-019-04030-1
Abstract: In order to improve action recognition accuracy, the discriminative kinematic descriptor and deep attention-pooled descriptor are proposed. Firstly, the optical flow field is transformed into a set of kinematic fields with more discriminativeness. Subsequently, two… read more here.
Keywords: descriptor; deep attention; discriminative kinematic; attention ... See more keywords
An Automated Framework for Histopathological Nucleus Segmentation with Deep Attention Integrated Networks.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2022.3233400
Abstract: Clinical management and accurate disease diagnosis are evolving from qualitative stage to the quantitative stage, particularly at the cellular level. However, the manual process of histopathological analysis is lab-intensive and time-consuming. Meanwhile, the accuracy is… read more here.
Keywords: deep attention; attention integrated; segmentation; integrated networks ... See more keywords
Interpretable Deep Attention Prior for Image Restoration and Enhancement
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Transactions on Computational Imaging"
DOI: 10.1109/tci.2023.3248943
Abstract: An inductive bias induced by an untrained network architecture has been shown to be effective as a deep image prior (DIP) in solving inverse imaging problems. However, it is still unclear as to what kind… read more here.
Keywords: deep attention; attention prior; attention; image ... See more keywords
DAHP: Deep Attention-Guided Hashing With Pairwise Labels
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems for Video Technology"
DOI: 10.1109/tcsvt.2021.3070129
Abstract: To address the problem of inadequate feature extraction and binary code discrete optimization faced by deep hashing methods using a relaxation-quantization strategy, a novel deep attention-guided hashing method with pairwise labels (DAHP) is proposed to… read more here.
Keywords: deep attention; pairwise; attention guided; pairwise labels ... See more keywords
Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2018.2813971
Abstract: Fine-grained visual recognition is an important problem in pattern recognition applications. However, it is a challenging task due to the subtle interclass difference and large intraclass variation. Recent visual attention models are able to automatically… read more here.
Keywords: attention; grained visual; visual recognition; fine grained ... See more keywords
Hyperspectral Image Classification Based on Deep Attention Graph Convolutional Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2021.3066485
Abstract: Hyperspectral images (HSIs) have gained high spectral resolution due to recent advances in spectral imaging technologies. This incurs problems, such as an increased data scale and an increased number of bands for HSIs, which results… read more here.
Keywords: attention; graph convolutional; based deep; graph ... See more keywords