Results 11 to 20 of about 1,582,815 (295)
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 code: https://github.com/OpenNLPLab/Vicinity-Vision ...
Weixuan Sun +9 more
openaire +6 more sources
Vision Transformer with Progressive Sampling [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Accepted to ICCV ...
Xiaoyu Yue +6 more
openaire +6 more sources
Comparing various vision transformer architectures for lung cancer classification
Discover Applied SciencesThis study presents a comprehensive evaluation of vision transformer-based architectures for lung histopathology image classification using the LC25000 dataset.
Sunil Kumar, Megha Jain, Manish Rai
doaj +2 more sources
Enhancing Security: Infused Hybrid Vision Transformer for Signature Verification [PDF]
IEEE AccessHandwritten signature verification is challenging because there is a huge variation between the orientation thickness and appearance of handwritten signatures.
Muhammad Ishfaq +3 more
doaj +2 more sources
Multiscale Vision Transformers [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Technical ...
Haoqi Fan 0001 +6 more
openaire +3 more sources
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 Prior works have proposed several strategies to reduce the computational cost of self-attention mechanism. Many of these works consider decomposing the self-attention procedure into regional and local feature extraction procedures that each incurs a much smaller computational complexity.
Ting Yao 0003 +5 more
openaire +3 more sources
International Journal of Computer Vision, 2023 We attempt to reduce the computational costs in vision transformers (ViTs), which increase quadratically in the token number. We present a novel training paradigm that trains only one ViT model at a time, but is capable of providing improved image recognition performance with various computational costs. Here, the trained ViT model, termed super vision
Mingbao Lin +6 more
openaire +3 more sources
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 Attention-based neural networks such as the Vision Transformer (ViT) have recently attained state-of-the-art results on many computer vision benchmarks. Scale is a primary ingredient in attaining excellent results, therefore, understanding a model's scaling properties is a key to designing future generations effectively.
Xiaohua Zhai +3 more
openaire +4 more sources
Building Extraction With Vision Transformer [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2022 Submitted to ...
Libo Wang +3 more
openaire +2 more sources
Advances in Neural Information Processing Systems 35, 2022 Human vision possesses a special type of visual processing systems called peripheral vision. Partitioning the entire visual field into multiple contour regions based on the distance to the center of our gaze, the peripheral vision provides us the ability to perceive various visual features at different regions.
Juhong Min +3 more
openaire +3 more sources