Results 1 to 10 of about 170,334 (258)
ViTT: Vision Transformer Tracker [PDF]
Sensors, 2021 This paper presents a new model for multi-object tracking (MOT) with a transformer. MOT is a spatiotemporal correlation task among interest objects and one of the crucial technologies of multi-unmanned aerial vehicles (Multi-UAV).
Xiaoning Zhu +4 more
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Review of Transformer in Computer Vision [PDF]
Jisuanji kexue, 2023 Transformer is an attention-based encoder-decoder architecture.Due to its long-range sequence modeling and parallel computing capability,Transformer have made a significant breakthrough in natural language processing and is gradually expanding to ...
CHEN Luoxuan, LIN Chengchuang, ZHENG Zhaoliang, MO Zefeng, HUANG Xinyi, ZHAO Gansen
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Remote Sensing, 2023 Efficient and accurate rice identification based on high spatial and temporal resolution remote sensing imagery is essential for achieving precision agriculture and ensuring food security.
Huiyao Xu, Jia Song, Yunqiang Zhu
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CSiT: A Multiscale Vision Transformer for Hyperspectral Image Classification
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 The hyperspectral image (HSI) has nearly continuous spectral information; thus, the target of interest can be accurately identified by the subtle details of spectral properties.
Wenxuan He +4 more
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Sensors, 2023 Semantic segmentation with deep learning networks has become an important approach to the extraction of objects from very high-resolution remote sensing images.
Jia Song, A-Xing Zhu, Yunqiang Zhu
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A Review of Transformer-Based Approaches for Image Captioning
Applied Sciences, 2023 Visual understanding is a research area that bridges the gap between computer vision and natural language processing. Image captioning is a visual understanding task in which natural language descriptions of images are automatically generated using ...
Oscar Ondeng, Heywood Ouma, Peter Akuon
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STHarDNet: Swin Transformer with HarDNet for MRI Segmentation
Applied Sciences, 2022 In magnetic resonance imaging (MRI) segmentation, conventional approaches utilize U-Net models with encoder–decoder structures, segmentation models using vision transformers, or models that combine a vision transformer with an encoder–decoder model ...
Yeonghyeon Gu +2 more
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Sensors, 2023 Understanding actions in videos remains a significant challenge in computer vision, which has been the subject of several pieces of research in the last decades.
Oumaima Moutik +6 more
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Transformer-based ripeness segmentation for tomatoes
Smart Agricultural Technology, 2023 With the recent development of computer vision technology, various computer vision techniques have been applied to agriculture. Recently, the Transformer network has been introduced to image recognition, which allows a different approach to extracting ...
Risa Shinoda +3 more
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Transformer architectures for computer vision: A comprehensive review and future research directions [PDF]
EPJ Web of ConferencesLong-range dependencies and contextual relationships in videos were captured by using Convolutional Neural Networks (CNNs) in past. Recently the use of Transformers is started for capturing the long-range dependencies and contextual relationships in ...
Ugile Tukaram, Uke Nilesh
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