Results 61 to 70 of about 1,512,599 (152)

Quantum Vision Transformers

Quantum
In this work, quantum transformers are designed and analysed in detail by extending the state-of-the-art classical transformer neural network architectures known to be very performant in natural language processing and image analysis. Building upon the previous work, which uses parametrised quantum circuits for data loading and orthogonal neural layers,
El Amine Cherrat, Iordanis Kerenidis, Natansh Mathur, Jonas Landman, Martin Strahm, Yun Yvonna Li   +5 more
openaire   +4 more sources

Transformer-based progressive residual network for single image dehazing

Frontiers in Neurorobotics, 2022
IntroductionThe seriously degraded fogging image affects the further visual tasks. How to obtain a fog-free image is not only challenging, but also important in computer vision.
Zhe Yang, Xiaoling Li, Xiaoling Li, Jinjiang Li, Jinjiang Li   +4 more
doaj   +1 more source

Towards Robust Vision Transformer

Recent advances on Vision Transformer (ViT) and its improved variants have shown that self-attention-based networks surpass traditional Convolutional Neural Networks (CNNs) in most vision tasks.
Mao, Xiaofeng, Xue, Hui, He, Yuan, Chen, Yuefeng, Li, Xiaodan, Ye, Shaokai, Duan, Ranjie, Qi, Gege   +7 more
core   +1 more source

Transforming vision into action

Vision Research, 2011
Traditionally, research on vision focused on its role in perception and our cognitive life. Except for the study of eye movements, which have been regarded as an information-seeking adjunct to visual perception, little attention was paid to the way in which vision is used to control our actions, particularly the movements of our hands and limbs.
openaire   +2 more sources

SE‐Swin: An improved Swin‐Transfomer network of self‐ensemble feature extraction framework for image retrieval

IET Image Processing
The Swin‐Transformer is a variant of the Vision Transformer, which constructs a hierarchical Transformer that computes representations with shifted windows and window multi‐head self‐attention.
Yixuan Xu, Xianbing Wang, Hua Zhang, Hai Lin   +3 more
doaj   +1 more source

A Hierarchical ViT With Dynamic Window Shift Unit and Curriculum Learning for Remote Sensing Image Scene Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
The remote sensing image (RSI) scene classification is currently a popular research topic among many remote sensing tasks. However, RSI scene classification still faces challenges such as complex multiscale key features concentrated in different local ...
Yi Liu, Xiang Wu, Jihuan Ren, Jiacun Wang, Yuming Bo, Yuanhao Wang   +5 more
doaj   +1 more source

A Sensorimotor Vision Transformer

CoRR
This paper presents the Sensorimotor Transformer (SMT), a vision model inspired by human saccadic eye movements that prioritize high-saliency regions in visual input to enhance computational efficiency and reduce memory consumption. Unlike traditional models that process all image patches uniformly, SMT identifies and selects the most salient patches ...
Konrad Gadzicki, Kerstin Schill, Christoph Zetzsche   +2 more
openaire   +3 more sources

Classification of Lung Diseases in X-Ray Images Using Transformer-Based Deep Learning Models

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
This research evaluates the performance of two Transformer models, the Vision Transformer (ViT) and Swin Transformer, in the analysis of thoracic X-ray images.
Nyoman Sarasuartha Mahajaya, Putu Desiana Wulaning Ayu, Roy Rudolf Huizen   +2 more
doaj   +1 more source

Depth Perception Using Various Vision Transformer [PDF]

EPJ Web of Conferences
Proper depth perception is one of the key requirements of three-dimensional understanding of scenes in the context of self-driving. The discussed manuscript defines a re-architecturing of VoxelNet with a dual attention paradigm (inspired by Vision ...
Kukreja Swetta, Parasar Deepa, Ritesh Sai Reddy Gowrugari, GaganSri Reddy Pyreddy, Shree Ram Gaikwad Rohan   +4 more
doaj   +1 more source

Hybrid model integrating LeViT transformer and distillation techniques for pattern detection and dance classification

Scientific Reports
Artificial intelligence (AI) has become an integral part of modern life, extending its impact into the preservation of cultural heritage. This study applies state-of-the-art vision transformer models for the classification of traditional Chinese dance ...
Yanyan Wang
doaj   +1 more source