NSTL国家科技图书文献中心

1. ViT-MVT: A Unified Vision Transformer Network for Multiple Vision Tasks NSTL国家科技图书文献中心

Tao Xie | Kun Dai ... - 《IEEE transactions on neural networks and learning systems》 - 2025,36(2) - 3027～3041 - 共15页

摘要： transformer (ViT)-MVT, built on a plain and nonhierarchical | mainstream vision* tasks concurrently using a unified* | single consolidated network. Our framework, vision | ViT, incorporates numerous visual tasks into a | various dataset domains. For the design of ViT-MVT, we

关键词： Task analysis | Transformers | Visualization | Computer architecture | Training | Semantic segmentation | Object detection

2. Embedded-ViT: A Framework for Embedded Deployment of Vision-Transformer in Medical Applications NSTL国家科技图书文献中心

Erik Ostrowski | Muhammad Shafique - 《Advances in Visual Computing,Part II》 - International Symposium on Visual Computing - 2025, - 371～382 - 共12页

摘要： the complexity of standard vision transformer (ViT | Transformer architectures have dramatically | becoming more popular in the computer vision* field, too* | transformer networks, but to our knowledge, very limited | -ViT* framework with which we can drastically reduce*

关键词： Semantic segmentation | Lightweight | Embedded deployment | CAD | Computer vision | Vision transformer

3. PDC-ViT: source camera identification using pixel difference convolution and vision transformer NSTL国家科技图书文献中心

Omar,Elharrouss | Younes,Akbari ... - 《Neural computing & applications》 - 2025,37(9) - 6933～6949 - 共17页

摘要： Convolution (PDC) with a Vision Transformer network (ViT | Vision Transformer network. Unlike traditional methods | PDC features into the Vision* Transformer network. To* | ), and named PDC-ViT. While the PDC acts as the | demonstrate the effectiveness of the PDC-ViT* approach, it*

关键词： Source camera identification | Deep learning method | Pixel difference convolution | Vision transformers network

4. Swelling-ViT: Rethink Data-Efficient Vision Transformer from Locality NSTL国家科技图书文献中心

Chuanrui Hu | Bin Chen ... - 《Pattern Recognition and Computer Vision,Part IV》 - Chinese Conference on Pattern Recognition and Computer Vision - 2025, - 32～46 - 共15页

摘要：In the domain of computer vision, Transformers | (ConvNets). Our work highlights Vision* Transformers (ViTs* | the development of our Swelling ViT* framework, an* | adaptive training strategy that initializes ViT* with a* | with Swelling ViT-B has yielded remarkable results

关键词： Data efficiency | Train from scratch | Vision transformer

5. AnisotropicBreast-ViT: Breast Cancer Classification in Ultrasound Images Using Anisotropic Filtering and Vision Transformer NSTL国家科技图书文献中心

Joao Otavio Bandeira... | Neilson P. Ribeiro ... - 《Intelligent Systems,Part III》 - Brazilian Conference on Intelligent Systems - 2025, - 95～109 - 共15页

摘要： augmentation, and Vision* Transformer to aid in the* | . This study introduces AnisotropicBreast-ViT, a method | . These findings suggest that AnisotropicBreast-ViT* has* | Breast cancer classification in ultrasound | images is a challenging and arduous task, primarily due

关键词： Breast cancer | Ultrasound | Vision transformer

6. Medical Report Generation from Medical Images Using Vision Transformer and Bart Deep Learning Architectures NSTL国家科技图书文献中心

Murat Ucan | Buket Kaya ... - 《Social Networks Analysis and Mining,Part IV》 - International Conference on Advances in Social Networks Analysis and Mining - 2025, - 257～267 - 共11页

摘要：. The proposed model consists of a Vision Transformer | (ViT) encoder and a Bidirectional Autoregressive | Transformer (BART) decoder. Training and testing on the | Generating medical reports from medical images | using traditional methods is a time-consuming process

关键词： Deep learning | Vision transformer | ViT | Bidirectional autoregressive transformer | BART | Medical report generation | Chest x-rays

7. Vit-CEM: A joint vision transformer and constrained energy minimization method for camouflage target detection in hyperspectral images NSTL国家科技图书文献中心

Jiale Zhao | Jiaju Ying ... - 《Tenth Symposium on Novel Optoelectronic Detection Technology and Applications,Part Two of Three Parts》 - Symposium on Novel Optoelectronic Detection Technology and Applications - 2025, - 1351133.1～1351133.10 - 共10页

摘要： target detection method with joint vision transformer | constraint method with the vision* transformer network* | vision transformer network to make it a powerful | (Vit) and constrained energy minimization is proposed | the Vit-CEM method can successfully detect artifacts

关键词： Hyperspectral imaging | Vision transformer | Constrained energy minimization | Target detection

8. ViT-SENet-Tom: machine learning-based novel hybrid squeeze–excitation network and vision transformer framework for tomato fruits classification NSTL国家科技图书文献中心

S M Masfequier Rahma... | S. M. Nuruzzaman,Nob...... - 《Neural computing & applications》 - 2025,37(9) - 6583～6600 - 共18页

摘要： vision transformer (ViT) model with squeeze and | learning (ML) framework, ViT-SENet-Tom, which is a hybrid | effective. The hybrid ViT-SENet framework employs encoders | Tomatoes are essential fruits in numerous | nations for their vast demand. It is very important to

关键词： Advance neural network | Food safety | Machine learning | Tomato fruit | Fruit classification | Vision transformer | SENet | Agriculture | Fresh fruits

9. Fusing CNNs and attention-mechanisms to improve real-time indoor Human Activity Recognition for classifying home-based physical rehabilitation exercises NSTL国家科技图书文献中心

Zaher M. | Ghoneim A.S.... - 《Computers in Biology and Medicine》 - 2025,184 - 109399～109399 - 共26页

摘要： Transformer (ViT) model. Additionally, we propose 12 hybrid | , This study integrates Computer Vision* and Human* | analysis, we evaluate 20 CNN-based models and one Vision | architectures that combine CNN-based models with ViT* in bi* | © 2024 Elsevier LtdPhysical rehabilitation

关键词： Continuous Wavelet Transform (CWT) | Deep learning | Mel-Frequency Cepstral Coefficients (MFCC) | Model fusion | Physical rehabilitation | Transfer learning | Vision Transformer (ViT)

10. AD-Lite Net: A Lightweight and Concatenated CNN Model for Alzheimer's Detection from MRI Images NSTL国家科技图书文献中心

Santanu Roy | Archit Gupta ... - 《Pattern Recognition,Part XII》 - International Conference on Pattern Recognition - 2025, - 1～16 - 共16页

摘要： Transformer (ViT) model by a significant margin. | existing CNN models, and one recent trend Vision | Alzheimer's Disease (AD) is a non-curable | progressive neurodegenerative disorder that affects the | human brain, leading to a decline in memory, cognitive

关键词： Alzheimer's disease detection | Magnetic resonance imaging (MRI) images | Convolutional neural network (CNN) | Attention-based models | Vision transformer (ViT)

摘要： transformer (ViT)-MVT, built on a plain and nonhierarchical | mainstream vision tasks concurrently using a unified | single consolidated network. Our framework, vision | ViT, incorporates numerous visual tasks into a | various dataset domains. For the design of ViT-MVT, we

关键词： Task analysis | Transformers | Visualization | Computer architecture | Training | Semantic segmentation | Object detection

摘要： the complexity of standard vision transformer (ViT | Transformer architectures have dramatically | becoming more popular in the computer vision field, too | transformer networks, but to our knowledge, very limited | -ViT framework with which we can drastically reduce

关键词： Semantic segmentation | Lightweight | Embedded deployment | CAD | Computer vision | Vision transformer

摘要： Convolution (PDC) with a Vision Transformer network (ViT | Vision Transformer network. Unlike traditional methods | PDC features into the Vision Transformer network. To | ), and named PDC-ViT. While the PDC acts as the | demonstrate the effectiveness of the PDC-ViT approach, it

关键词： Source camera identification | Deep learning method | Pixel difference convolution | Vision transformers network

摘要：In the domain of computer vision, Transformers | (ConvNets). Our work highlights Vision Transformers (ViTs | the development of our Swelling ViT framework, an | adaptive training strategy that initializes ViT with a | with Swelling ViT-B has yielded remarkable results

关键词： Data efficiency | Train from scratch | Vision transformer

摘要： augmentation, and Vision Transformer to aid in the | . This study introduces AnisotropicBreast-ViT, a method | . These findings suggest that AnisotropicBreast-ViT has | Breast cancer classification in ultrasound | images is a challenging and arduous task, primarily due

关键词： Breast cancer | Ultrasound | Vision transformer

摘要：. The proposed model consists of a Vision Transformer | (ViT) encoder and a Bidirectional Autoregressive | Transformer (BART) decoder. Training and testing on the | Generating medical reports from medical images | using traditional methods is a time-consuming process

关键词： Deep learning | Vision transformer | ViT | Bidirectional autoregressive transformer | BART | Medical report generation | Chest x-rays

摘要： target detection method with joint vision transformer | constraint method with the vision transformer network | vision transformer network to make it a powerful | (Vit) and constrained energy minimization is proposed | the Vit-CEM method can successfully detect artifacts

关键词： Hyperspectral imaging | Vision transformer | Constrained energy minimization | Target detection

摘要： vision transformer (ViT) model with squeeze and | learning (ML) framework, ViT-SENet-Tom, which is a hybrid | effective. The hybrid ViT-SENet framework employs encoders | Tomatoes are essential fruits in numerous | nations for their vast demand. It is very important to

关键词： Advance neural network | Food safety | Machine learning | Tomato fruit | Fruit classification | Vision transformer | SENet | Agriculture | Fresh fruits

摘要： Transformer (ViT) model. Additionally, we propose 12 hybrid | , This study integrates Computer Vision and Human | analysis, we evaluate 20 CNN-based models and one Vision | architectures that combine CNN-based models with ViT in bi | © 2024 Elsevier LtdPhysical rehabilitation

关键词： Continuous Wavelet Transform (CWT) | Deep learning | Mel-Frequency Cepstral Coefficients (MFCC) | Model fusion | Physical rehabilitation | Transfer learning | Vision Transformer (ViT)

摘要： Transformer (ViT) model by a significant margin. | existing CNN models, and one recent trend Vision | Alzheimer's Disease (AD) is a non-curable | progressive neurodegenerative disorder that affects the | human brain, leading to a decline in memory, cognitive

关键词： Alzheimer's disease detection | Magnetic resonance imaging (MRI) images | Convolutional neural network (CNN) | Attention-based models | Vision transformer (ViT)

4008-161-200 800-990-8900

国家科技图书文献中心

摘要： transformer (ViT)-MVT, built on a plain and nonhierarchical | mainstream vision* tasks concurrently using a unified* | single consolidated network. Our framework, vision | ViT, incorporates numerous visual tasks into a | various dataset domains. For the design of ViT-MVT, we

摘要： the complexity of standard vision transformer (ViT | Transformer architectures have dramatically | becoming more popular in the computer vision* field, too* | transformer networks, but to our knowledge, very limited | -ViT* framework with which we can drastically reduce*

摘要： Convolution (PDC) with a Vision Transformer network (ViT | Vision Transformer network. Unlike traditional methods | PDC features into the Vision* Transformer network. To* | ), and named PDC-ViT. While the PDC acts as the | demonstrate the effectiveness of the PDC-ViT* approach, it*

摘要：In the domain of computer vision, Transformers | (ConvNets). Our work highlights Vision* Transformers (ViTs* | the development of our Swelling ViT* framework, an* | adaptive training strategy that initializes ViT* with a* | with Swelling ViT-B has yielded remarkable results

摘要： augmentation, and Vision* Transformer to aid in the* | . This study introduces AnisotropicBreast-ViT, a method | . These findings suggest that AnisotropicBreast-ViT* has* | Breast cancer classification in ultrasound | images is a challenging and arduous task, primarily due

摘要： target detection method with joint vision transformer | constraint method with the vision* transformer network* | vision transformer network to make it a powerful | (Vit) and constrained energy minimization is proposed | the Vit-CEM method can successfully detect artifacts

摘要： Transformer (ViT) model. Additionally, we propose 12 hybrid | , This study integrates Computer Vision* and Human* | analysis, we evaluate 20 CNN-based models and one Vision | architectures that combine CNN-based models with ViT* in bi* | © 2024 Elsevier LtdPhysical rehabilitation