Results 21 to 30 of about 4,993 (66)

RT-ViT: Real-Time Monocular Depth Estimation Using Lightweight Vision Transformers

Sensors, 2022
The latest research in computer vision highlighted the effectiveness of the vision transformers (ViT) in performing several computer vision tasks; they can efficiently understand and process the image globally unlike the convolution which processes the ...
Hatem Ibrahem, Ahmed Salem, Hyun-Soo Kang   +2 more
doaj   +1 more source

Leveraging Transfer Learning for Accurate CRP Level Prediction in Diabetic Patients

Zanco Journal of Pure and Applied Sciences
This study addresses the challenge of predicting C-reactive protein (CRP) levels in patients with type 2 diabetes mellitus by integrating tabular-to-image transformation techniques with transfer learning architectures.
Alaa J. Albaqal, Mardin A. Anwar
doaj   +1 more source

Transformer-Based Fusion of Body and Context for Emotion Recognition [PDF]

EPJ Web of Conferences
This paper investigates using image-based features, combining body posture and context, to automatically detect emotions in natural settings. We focus on seven emotions: happy, sad, disgust, neutral, surprise, anger, and fear , from the NCAER dataset. We
Elkorchi Merieme, Hdioud Boutaina, Thami Rachid Oulad Haj, Merzouk Safae   +3 more
doaj   +1 more source

Hybrid Quantum Vision Transformers for Event Classification in High Energy Physics

Axioms
Models based on vision transformer architectures are considered state-of-the-art when it comes to image classification tasks. However, they require extensive computational resources both for training and deployment.
Eyup B. Unlu, Marçal Comajoan Cara, Gopal Ramesh Dahale, Zhongtian Dong, Roy T. Forestano, Sergei Gleyzer, Daniel Justice, Kyoungchul Kong, Tom Magorsch, Konstantin T. Matchev, Katia Matcheva   +10 more
doaj   +1 more source

Evaluation of vision transformers for the detection of fullness of garbage bins for efficient waste management

Frontiers in Artificial Intelligence
Efficient waste management is crucial for urban environments to maintain cleanliness, reduce environmental impact, and optimize resource allocation. Traditional waste collection systems often rely on scheduled pickups or manual inspections, leading to ...
Parakram Singh Tanwer, Shishir Maheshwari, Sushree Behera, Amit Chauhan, T. Sunil Kumar   +4 more
doaj   +1 more source

Transformer With Linear-Window Attention for Feature Matching

IEEE Access, 2023
A transformer can capture long-term dependencies through an attention mechanism, and hence, can be applied to various vision tasks. However, its secondary computational complexity is a major obstacle in vision tasks that require accurate predictions.
Zhiwei Shen, Bin Kong, Xiaoyu Dong
doaj   +1 more source

Transformer-based progressive residual network for single image dehazing

Frontiers in Neurorobotics, 2022
IntroductionThe seriously degraded fogging image affects the further visual tasks. How to obtain a fog-free image is not only challenging, but also important in computer vision.
Zhe Yang, Xiaoling Li, Xiaoling Li, Jinjiang Li, Jinjiang Li   +4 more
doaj   +1 more source

SE‐Swin: An improved Swin‐Transfomer network of self‐ensemble feature extraction framework for image retrieval

IET Image Processing
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, Xianbing Wang, Hua Zhang, Hai Lin   +3 more
doaj   +1 more source

A Hierarchical ViT With Dynamic Window Shift Unit and Curriculum Learning for Remote Sensing Image Scene Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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, Xiang Wu, Jihuan Ren, Jiacun Wang, Yuming Bo, Yuanhao Wang   +5 more
doaj   +1 more source

Classification of Lung Diseases in X-Ray Images Using Transformer-Based Deep Learning Models

Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI)
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, Putu Desiana Wulaning Ayu, Roy Rudolf Huizen   +2 more
doaj   +1 more source