Results 71 to 80 of about 25,011 (267)
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 +3 more
doaj +1 more source
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 +5 more
doaj +1 more source
The PRIMA Thesaurus for Materials Science and Engineering
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa +8 more
wiley +1 more source
Classification of Lung Diseases in X-Ray Images Using Transformer-Based Deep Learning Models
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 +2 more
doaj +1 more source
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 +5 more
wiley +1 more source
A Sensorimotor Vision Transformer
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 +2 more
openaire +2 more sources
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
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
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

