Results 31 to 40 of about 8,876 (216)
Swin-Pose: Swin Transformer Based Human Pose Estimation
2022 IEEE 5th International Conference on Multimedia Information Processing and Retrieval (MIPR), 2022 Convolutional neural networks (CNNs) have been widely utilized in many computer vision tasks. However, CNNs have a fixed reception field and lack the ability of long-range perception, which is crucial to human pose estimation. Due to its capability to capture long-range dependencies between pixels, transformer architecture has been adopted to computer ...
Zinan Xiong +4 more
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Swin-transformer block (ST-B).
, 2023 The health of the trees in the forest affects the ecological environment, so timely detection of Standing Dead Trees (SDTs) plays an important role in forest management.
Siyu Han (4614106) +5 more
core +1 more source
Facial Expression Recognition with Swin Transformer
CoRR, 2022 The task of recognizing human facial expressions plays a vital role in various human-related systems, including health care and medical fields. With the recent success of deep learning and the accessibility of a large amount of annotated data, facial expression recognition research has been mature enough to be utilized in real-world scenarios with ...
Jun-Hwa Kim, Namho Kim, Chee Sun Won
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Self-Supervised Learning with Swin Transformers
CoRR, 2021 We are witnessing a modeling shift from CNN to Transformers in computer vision. In this work, we present a self-supervised learning approach called MoBY, with Vision Transformers as its backbone architecture. The approach basically has no new inventions, which is combined from MoCo v2 and BYOL and tuned to achieve reasonably high accuracy on ImageNet ...
Zhenda Xie +6 more
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A Swin Transformer-based model for mosquito species identification
Scientific Reports, 2022 Mosquito transmit numbers of parasites and pathogens resulting in fatal diseases. Species identification is a prerequisite for effective mosquito control. Existing morphological and molecular classification methods have evitable disadvantages.
De-zhong Zhao +8 more
doaj +1 more source
SwinIR: Image Restoration Using Swin Transformer [PDF]
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), 2021 Image restoration is a long-standing low-level vision problem that aims to restore high-quality images from low-quality images (e.g., downscaled, noisy and compressed images). While state-of-the-art image restoration methods are based on convolutional neural networks, few attempts have been made with Transformers which show impressive performance on ...
Jingyun Liang +5 more
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Enhancing medical image segmentation with a multi-transformer U-Net [PDF]
PeerJVarious segmentation networks based on Swin Transformer have shown promise in medical segmentation tasks. Nonetheless, challenges such as lower accuracy and slower training convergence have persisted. To tackle these issues, we introduce a novel approach
Yongping Dan +3 more
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Comparative analysis of transformer architectures for brain tumor classification [PDF]
Exploration of MedicineAim: Early and accurate diagnosis of brain tumors is critical for treatment success, but manual magnetic resonance imaging (MRI) interpretation has limitations.
Yigitcan Cakmak, Ishak Pacal
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Swin-APT: An Enhancing Swin-Transformer Adaptor for Intelligent Transportation
Applied Sciences, 2023 Artificial Intelligence has been widely applied in intelligent transportation systems. In this work, Swin-APT, a deep learning-based approach for semantic segmentation and object detection in intelligent transportation systems is presented. Swin-APT includes a lightweight network and a multiscale adapter network designed for image semantic segmentation
Yunzhuo Liu +4 more
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Swin on Axes: Extending Swin Transformers to Quadtree Image Representations [PDF]
2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW)In recent years, Transformer models have revolutionized machine learning. While this has resulted in impressive re-sults in the field of Natural Language Processing, Computer Vision quickly stumbled upon computation and memory problems due to the high resolution and dimensionality of the input data. This is particularly true for video, where the number
Marc Oliu +3 more
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