Results 71 to 80 of about 33,786 (306)

Interpretability-Aware Vision Transformer

CoRR, 2023
Vision Transformers (ViTs) have become prominent models for solving various vision tasks. However, the interpretability of ViTs has not kept pace with their promising performance. While there has been a surge of interest in developing {\it post hoc} solutions to explain ViTs' outputs, these methods do not generalize to different downstream tasks and ...
Yao Qiang, Chengyin Li, Prashant Khanduri, Dongxiao Zhu   +3 more
openaire   +2 more sources

$E(2)$-Equivariant Vision Transformer

, 2023
Vision Transformer (ViT) has achieved remarkable performance in computer vision. However, positional encoding in ViT makes it substantially difficult to learn the intrinsic equivariance in data.
Yang, Kaifan, He, Fengxiang, Xu, Renjun, Liu, Ke   +3 more
core   +1 more source

Ontology‐Aligned Structuring and Reuse of Multimodal Materials Data and Workflows Toward Automatic Reproduction

Advanced Engineering Materials, EarlyView.
Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari, Abril Azocar Guzman, Sarath Menon, Stefan Sandfeld, Tilmann Hickel, Markus Stricker   +5 more
wiley   +1 more source

Weather Image Recognition Using Vision Transformer

, 2023
Weather significantly impacts human activities, and accurate weather recognition is crucial to mitigate the risks associated with severe weather conditions. In this research project, we propose Vision Transformer for weather image recognition.
Lim, Kian Ming, Tan, Jun Zhi, Lim, Jit Yan, Lee, Chin Poo   +3 more
core   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Grafting Vision Transformers

2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
Vision Transformers (ViTs) have recently become the state-of-the-art across many computer vision tasks. In contrast to convolutional networks (CNNs), ViTs enable global information sharing even within shallow layers of a network, i.e., among high-resolution features. However, this perk was later overlooked with the success of pyramid architectures such
Jongwoo Park 0003, Kumara Kahatapitiya, Donghyun Kim 0006, Shivchander Sudalairaj, Quanfu Fan, Michael S. Ryoo   +5 more
openaire   +2 more sources

Towards Robust Vision Transformer

, 2022
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

Liquid Phase Transmission Electron Microscopy: A Window into the Early Stages of Complex Material Formation

Advanced Functional Materials, EarlyView.
Liquid‐phase transmission electron microscopy enables direct observation of nucleation and growth processes in solution. This review is dedicated to the remembrance of Helmut Cölfen and highlights recent studies on complex materials—oxides, biominerals, organic–inorganic crystals—which were central to his research activity. It summarizes key milestones,
Charles Sidhoum, Vinavadini Ramnarain, Nathaly Ortiz Peña, Dris Ihiawakrim, Clément Sanchez, Ovidiu Ersen   +5 more
wiley   +1 more source

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