Results 91 to 100 of about 1,512,599 (152)

Vision Transformers for Computer Go

Motivated by the success of transformers in various fields, such as language understanding and image analysis, this investigation explores their application in the context of the game of Go. In particular, our study focuses on the analysis of the Transformer in Vision.
Amani Sagri, Tristan Cazenave, Jérôme Arjonilla, Abdallah Saffidine   +3 more
openaire   +3 more sources

Blending Anti-Aliasing into Vision Transformer

, 2021
The transformer architectures, based on self-attention mechanism and convolution-free design, recently found superior performance and booming applications in computer vision.
Shao, Hao, Zhu, Yi, Li, Mu, Qian, Shengju, Jia, Jiaya   +4 more
core  

A self attention based deep learning framework for accurate and efficient dental disease detection in OPG radiographs

Scientific Reports
Oral diseases are increasing now-a-days and there is a high demand for the automatic diagnostic system that helps the clinician to detect these oral diseases with more accuracy and reduced human error.
Ramasubramanian Bhoopalan, S. Mirdula, Priyadharshini Kannusamy, D. Gayathri, D. Manikandan, Krishnaraj Ramaswamy   +5 more
doaj   +1 more source

Brain Stroke Classification Using CT Scans with Transformer-Based Models and Explainable AI

Diagnostics
Background & Objective: Stroke remains a leading cause of mortality and long-term disability worldwide, demanding rapid and accurate diagnosis to improve patient outcomes.
Shomukh Qari, Maha A. Thafar
doaj   +1 more source

Retina Vision Transformer (RetinaViT): Introducing Scaled Patches into Vision Transformers

CoRR
Humans see low spatial frequency components before high spatial frequency components. Drawing on this neuroscientific inspiration, we investigate the effect of introducing patches from different spatial frequencies into Vision Transformers (ViTs). We name this model Retina Vision Transformer (RetinaViT) due to its inspiration from the human visual ...
Yuyang Shu, Michael E. Bain
openaire   +3 more sources

EEViT: Efficient Enhanced Vision Transformer Architectures with Information Propagation and Improved Inductive Bias

AI
The Transformer architecture has been the foundational cornerstone of the recent AI revolution, serving as the backbone of Large Language Models, which have demonstrated impressive language understanding and reasoning capabilities.
Rigel Mahmood, Sarosh Patel, Khaled Elleithy   +2 more
doaj   +1 more source

MulT: An End-to-End Multitask Learning Transformer

We propose an end-to-end Multitask Learning Transformer framework, named MulT, to simultaneously learn multiple high-level vision tasks, including depth estimation, semantic segmentation, reshading, surface normal estimation, 2D keypoint detection, and ...
Bhattacharjee, Deblina, Salzmann, Mathieu, Suesstrunk, Sabine, Zhang, Tong   +3 more
core   +1 more source

MGFR-ViT: A Multi-Scale Gated Feature Refinement Vision Transformer for Vibration-Based Fault Diagnosis

Sensors
To address the limited extraction of local fault features, ineffective fusion of multi-scale fault information and interference from redundant noise in vibration-based fault diagnosis of rolling bearings and gears under complex operating conditions, a ...
Yan Yan, Ting Shang, Kun Jia, Songnan Yang, Haiyan Cheng, Yuxing Li, Wei Quan   +6 more
doaj   +1 more source

Bridging in contaminated transformer oil under DC and AC electric field

, 2013
One of the key components in high voltage transmission and distribution systems are power transformers and their consistent operation is of utmost importance to energy utilities and users.
Wilson, G, Mahmud, S., Jarman, P, Golosnoy, I. O., Mahmud, S, Chen, G., Wilson, G., Golosnoy, I O, Chen, G, Jarman, P.   +9 more
core   +1 more source

Exploring Vision Transformers and Convolution Neural Networks for the Thermal Image Classification of Volcanic Activity

Applied Sciences
This paper addresses the classification of images depicting the eruptive activity of Mount Etna that were captured by a network of ground-based thermal cameras.
Giuseppe Nunnari, Sonia Calvari
doaj   +1 more source