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   Articles with "vision transformers" as a keyword



Vision transformers for rice leaf disease detection and severity estimation: a precision agriculture approach

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recommendations! Published in 2025 at "Journal of the Saudi Society of Agricultural Sciences"

DOI: 10.1007/s44447-025-00007-w

Abstract: Rice leaf diseases represent a major hazard to rice production worldwide, affecting the output, integrity, and nutritional value of the crop. Conventional methods are time-consuming, costly, and often inaccessible to smallholder farmers, necessitating scalable and… read more here.

Keywords: disease; severity; rice leaf; vision transformers ... See more keywords

Efficient attention vision transformers for monocular depth estimation on resource-limited hardware

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-06112-8

Abstract: Vision Transformers show important results in the current Deep Learning technological landscape, being able to approach complex and dense tasks, for instance, Monocular Depth Estimation. However, in the transformer architecture, the attention module introduces a… read more here.

Keywords: depth estimation; vision transformers; monocular depth; efficient attention ... See more keywords

Advanced fault diagnosis in milling cutting tools using vision transformers with semi-supervised learning and uncertainty quantification

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recommendations! Published in 2025 at "Scientific Reports"

DOI: 10.1038/s41598-025-26550-8

Abstract: This study proposes a semi-supervised fault diagnosis framework based on vision transformers (ViTs) to enhance the diagnostic accuracy and generalization in machine cutting tools (MCT), particularly under the constraint of limited labeled data, a common… read more here.

Keywords: diagnosis; cutting tools; semi supervised; fault diagnosis ... See more keywords

Vision Transformers for Vein Biometric Recognition

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recommendations! Published in 2023 at "IEEE Access"

DOI: 10.1109/access.2023.3252009

Abstract: In October 2020, Google researchers present a promising Deep Learning architecture paradigm for Computer Vision that outperforms the already standard Convolutional Neural Networks (CNNs) on multiple image recognition state-of-the-art datasets: Vision Transformers (ViTs). Based on… read more here.

Keywords: transformers vein; fine tuned; biometric recognition; vision transformers ... See more keywords

A Real-Time Vision Transformers-Based System for Enhanced Driver Drowsiness Detection and Vehicle Safety

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2024.3522111

Abstract: Drowsy driving is a leading cause of fatal traffic accidents worldwide. Drowsy driving has emerged from modern societal trends such as long working hours, heavy reliance on vehicles, and insufficient sleep. Despite considerable efforts by… read more here.

Keywords: vision transformers; system; drowsiness detection; driver drowsiness ... See more keywords

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

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3571735

Abstract: 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… read more here.

Keywords: survey; transformers vision; vision; vision transformers ... See more keywords

Enhancing Vision Transformers for Facial Expression Recognition

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recommendations! Published in 2025 at "IEEE Access"

DOI: 10.1109/access.2025.3598917

Abstract: Facial expression recognition (FER) remains a challenging problem due to subtle intra-class variations, strong inter-class similarities, and external factors including pose variations, illumination changes, and occlusions. While vision transformers (ViTs) have demonstrated success in general… read more here.

Keywords: vision transformers; facial expression; expression recognition; vision ... See more keywords

Heuristical Comparison of Vision Transformers Against Convolutional Neural Networks for Semantic Segmentation on Remote Sensing Imagery

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recommendations! Published in 2024 at "IEEE Sensors Journal"

DOI: 10.1109/jsen.2025.3557362

Abstract: Vision Transformers (ViTs) have recently brought a new wave of research in the field of computer vision. These models have done particularly well in the field of image classification and segmentation. Research on semantic and… read more here.

Keywords: comparison; segmentation; segmentation remote; semantic segmentation ... See more keywords

Personalized Speech Emotion Recognition in Human-Robot Interaction Using Vision Transformers

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recommendations! Published in 2024 at "IEEE Robotics and Automation Letters"

DOI: 10.1109/lra.2025.3554949

Abstract: Emotions are an essential element in human verbal communication, therefore it is important to understand individuals' affect during human-robot interaction (HRI). This letter investigates the application of vision transformer models, namely ViT (Vision Transformers) and… read more here.

Keywords: human robot; speech emotion; vision; vision transformers ... See more keywords

Sparse-to-Dense Training: A Novel Training Scheme to Enhance Vision Transformers

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recommendations! Published in 2025 at "IEEE Transactions on Circuits and Systems for Video Technology"

DOI: 10.1109/tcsvt.2025.3586550

Abstract: As Vision Transformers (ViTs) become increasingly popular in various vision tasks, one may question: if a new training scheme for ViTs exists that can improve performance without increasing training and inference computation cost? In this… read more here.

Keywords: training; vision; training scheme; vision transformers ... See more keywords

Adaptive Locality Guidance: Using Locality Guidance to Initialize the Learning of Vision Transformers on Tiny Datasets

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recommendations! Published in 2025 at "IEEE Transactions on Neural Networks and Learning Systems"

DOI: 10.1109/tnnls.2024.3515076

Abstract: While we keep working toward leveraging the benefits of vision transformers (VTs) on small datasets, convolutional neural networks (CNNs) still remain the choice of preference when extensive training data is unavailable. As studies show that… read more here.

Keywords: vision transformers; guidance; tiny datasets; locality guidance ... See more keywords