Transformers for Vision: A Survey on Innovative Methods for Computer Vision

Transformers for Vision: A Survey on Innovative Methods for Computer Vision

Transformers have emerged as a groundbreaking architecture in the field of computer vision, offering a compelling alternative to traditional convolutional neural networks (CNNs) by enabling the modeling of long-range dependencies and global context through self-attention mechanisms. Originally devel...

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Bibliographic Details
Main Authors: Balamurugan Palanisamy, Vikas Hassija, Arpita Chatterjee, Arpita Mandal, Debanshi Chakraborty, Amit Pandey, G. S. S. Chalapathi, Dhruv Kumar
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Action recognition
computer vision
convolutional neural networks (CNNs)
efficient transformers
image classification
object detection
Online Access:https://ieeexplore.ieee.org/document/11007557/
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