[HTML][HTML] A Framework for Integrating Vision Transformers with Digital Twins in Industry 5.0 Context

A Kovari - Machines, 2025 - mdpi.com
The transition from Industry 4.0 to Industry 5.0 gives more prominence to human-centered
and sustainable manufacturing practices. This paper proposes a conceptual design …

Steel Surface Defect Detection Using Learnable Memory Vision Transformer.

STK Ayon, FM Siraj, J Uddin - Computers, Materials & …, 2025 - search.ebscohost.com
This study investigates the application of Learnable Memory Vision Transformers (LMViT) for
detecting metal surface flaws, comparing their performance with traditional CNNs …

CNNtention: Can CNNs do better with Attention?

J Glattki, N Kapila, T Rathi - arxiv preprint arxiv:2412.11657, 2024 - arxiv.org
Convolutional Neural Networks (CNNs) have been the standard for image classification
tasks for a long time, but more recently attention-based mechanisms have gained traction …

Image recognition and intelligent space allocation strategy optimization in interior architectural design

Y Hu, R Li, Z Liu, H Li - Engineering Research Express, 2025 - iopscience.iop.org
In current interior architectural design, the application of image recognition technology is not
sufficient, and the optimization of intelligent space allocation strategy faces many …

Convolutional and dynamical spintronic neural networks

E Plouet - 2024 - theses.hal.science
This thesis addresses the development of spintronic components for neuromorphic
computing, a novel approach aimed at reducing the significant energy consumption of AI …

[PDF][PDF] Classification of Pneumonia from CXR scans using an Ensemble of Weighted CNNs, Attention block, and a Visual Transformer—EWCAVIT

A Jumabekov - files.osf.io
Pneumonia is a serious respiratory disease that causes high mortality rates worldwide,
especially in children under the age of 5 and the elderly. Early detection of pneumonia is …