Results 61 to 70 of about 1,457,471 (199)
Mix-ViT : mixing attentive vision transformer for ultra-fine-grained visual categorization
Ultra-fine-grained visual categorization (ultra-FGVC) moves down the taxonomy level to classify sub-granularity categories of fine-grained objects. This inevitably poses a challenge, i.e., classifying highly similar objects with limited samples, which ...
Yu, Xiaohan +3 more
core +1 more source
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 +4 more
wiley +1 more source
Pyramid Vision Transformer: A Versatile Backbone for Dense Prediction without Convolutions
Although convolutional neural networks (CNNs) have achieved great success in computer vision, this work investigates a simpler, convolution-free backbone network use-fid for many dense prediction tasks.
Deng-Ping Fan +17 more
core +1 more source
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
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
FSwin Transformer: Feature-Space Window Attention Vision Transformer for Image Classification
The vision transformer (ViT) with global self-attention exhibits quadratic computational complexity that depends on the image size. To address this issue, window-based self-attention ViT limits attention area to a specific window, thereby mitigating the ...
Dayeon Yoo, Jeesu Kim, Jinwoo Yoo
doaj +1 more source
The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling +15 more
wiley +1 more source
Residual adhesive after electrode loading in adhesive‐assisted resistance spot welding is quantified through a traceable experimental‐to‐digital workflow. Chromatic confocal topography provides calibrated surface‐height data, while OpenCV detects the electrode imprint and integrates adhesive height into comparable volume metrics.
Sung‐Min Wi, Jiangdong Zhao
wiley +1 more source
A customised vision transformer for accurate detection and classification of Java Plum leaf disease [PDF]
Vision Transformer (ViT) has recently attracted significant attention for its performance in image classification. However, studies have yet to explore its potential in detecting and classifying plant leaf disease.
Bhowmik, Auvick Chandra +5 more
core +1 more source
Depth Perception Using Various Vision Transformer [PDF]
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 +4 more
doaj +1 more source

