Results 11 to 20 of about 15,271 (229)
DarSwin: Distortion Aware Radial Swin Transformer
2023 IEEE/CVF International Conference on Computer Vision (ICCV), 2023 Wide-angle lenses are commonly used in perception tasks requiring a large field of view. Unfortunately, these lenses produce significant distortions making conventional models that ignore the distortion effects unable to adapt to wide-angle images.
Afrasiyabi, Arman +5 more
core +2 more sources
SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction
, 2022 Packaged fresh-cut lettuce is widely consumed as a major component of vegetable salad owing to its high nutrition, freshness, and convenience. However, enzymatic browning discoloration on lettuce cut edges significantly reduces product quality and shelf ...
Luo, Yaguang +4 more
core +2 more sources
Tooth Type Enhanced Transformer for Children Caries Diagnosis on Dental Panoramic Radiographs
Diagnostics, 2023 The objective of this study was to introduce a novel deep learning technique for more accurate children caries diagnosis on dental panoramic radiographs.
Xiaojie Zhou +6 more
doaj +1 more source
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
doaj +1 more source
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 The vision community is witnessing a modeling shift from CNNs to Transformers, where pure Transformer architectures have attained top accuracy on the major video recognition benchmarks. These video models are all built on Transformer layers that globally connect patches across the spatial and temporal dimensions.
Liu, Ze +6 more
openaire +2 more sources
Swin Transformer Assisted Prior Attention Network for Medical Image Segmentation
Applied Sciences, 2022 Transformer complements convolutional neural network (CNN) has achieved better performance than improved CNN-based methods. Specially, Transformer is utilized to be combined with U-shaped structure, skip-connections, encoder, and even them all together ...
Zhihao Liao, Neng Fan, Kai Xu
doaj +1 more source
Entropy, 2022 Convolutional neural networks have long dominated semantic segmentation of very-high-resolution (VHR) remote sensing (RS) images. However, restricted by the fixed receptive field of convolution operation, convolution-based models cannot directly obtain ...
Yufen Xu, Shangbo Zhou, Yuhui Huang
doaj +1 more source
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 ...
Xiong, Zinan +4 more
openaire +2 more sources
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
doaj +1 more source
A Swin transformer and MLP based method for identifying cherry ripeness and decay
Frontiers in Physics, 2023 Cherries are a nutritionally beneficial and economically significant crop, with fruit ripeness and decay (rot or rupture) being critical indicators in the cherry sorting process.
Ke Song, Jiwen Yang, Guohui Wang
doaj +1 more source