Results 31 to 40 of about 7,252 (198)

Swin-APT: An Enhancing Swin-Transformer Adaptor for Intelligent Transportation

Applied Sciences, 2023
Artificial Intelligence has been widely applied in intelligent transportation systems. In this work, Swin-APT, a deep learning-based approach for semantic segmentation and object detection in intelligent transportation systems is presented. Swin-APT includes a lightweight network and a multiscale adapter network designed for image semantic segmentation
Yunzhuo Liu, Chunjiang Wu, Yuting Zeng, Keyu Chen, Shijie Zhou   +4 more
openaire   +2 more sources

Water index and Swin Transformer Ensemble (WISTE) for water body extraction from multispectral remote sensing images

GIScience & Remote Sensing, 2023
Automatic surface water body mapping using remote sensing technology is greatly meaningful for studying inland water dynamics at regional to global scales.
Donghui Ma, Liguang Jiang, Jie Li, Yun Shi   +3 more
doaj   +1 more source

Enhancing medical image segmentation with a multi-transformer U-Net [PDF]

PeerJ
Various segmentation networks based on Swin Transformer have shown promise in medical segmentation tasks. Nonetheless, challenges such as lower accuracy and slower training convergence have persisted. To tackle these issues, we introduce a novel approach
Yongping Dan, Weishou Jin, Xuebin Yue, Zhida Wang   +3 more
doaj   +2 more sources

Evaluation and Mitigation of Faults Affecting Swin Transformers

2023 IEEE 29th International Symposium on On-Line Testing and Robust System Design (IOLTS), 2023
In the last decade, a huge effort has been spent on assessing the reliability of Convolutional Neural networks (CNNs), probably the most popular architecture for image classification tasks. However, modern Deep Neural Networks (DNNs) are rapidly overtaking CNNs, as state-of-the-art results for many tasks are achieved with the Transformers, innovative ...
Gabriele Gavarini, Annachiara Ruospo, Ernesto Sanchez   +2 more
openaire   +2 more sources

SQ-Swin: a Pretrained Siamese Quadratic Swin Transformer for Lettuce Browning Prediction

CoRR, 2022
Packaged fresh-cut lettuce is widely consumed as a major component of vegetable salad owing to its high nutrition, freshness, and convenience. However, enzymatic browning discoloration on lettuce cut edges significantly reduces product quality and shelf life. While there are many research and breeding efforts underway to minimize browning, the progress
Dayang Wang, Boce Zhang, Yongshun Xu, Yaguang Luo, Hengyong Yu   +4 more
openaire   +2 more sources

Classification and Model Explanation of Traditional Dwellings Based on Improved Swin Transformer

Buildings
The extraction of features and classification of traditional dwellings plays significant roles in preserving and ensuring the sustainable development of these structures.
Shangbo Miao, Chenxi Zhang, Yushun Piao, Yalin Miao   +3 more
doaj   +1 more source

Center Point Target Detection Algorithm Based on Improved Swin Transformer [PDF]

Jisuanji kexue
Aiming at the shortcomings of Swin Transformer in extracting local feature information and expressing features,this paper proposes a center point target detection algorithm based on improved Swin Transformer to improve its performance in target detection.
LIU Jiasen, HUANG Jun
doaj   +1 more source

A wheat spike detection method based on Transformer

Frontiers in Plant Science, 2022
Wheat spike detection has important research significance for production estimation and crop field management. With the development of deep learning-based algorithms, researchers tend to solve the detection task by convolutional neural networks (CNNs ...
Qiong Zhou, Qiong Zhou, Qiong Zhou, Ziliang Huang, Ziliang Huang, Shijian Zheng, Shijian Zheng, Lin Jiao, Lin Jiao, Liusan Wang, Rujing Wang, Rujing Wang   +11 more
doaj   +1 more source

Leveraging Big Multitemporal Multisource Satellite Data and Artificial Intelligence for the Detection of Complex and Invisible Features: The Case of Extensive Irrigation Mapping

Archaeological Prospection, EarlyView.
ABSTRACT The detection of buried or obscured archaeological features remains a central challenge in landscape archaeology, particularly in the irrigated floodplains of Mesopotamia where levees and canals formed the basis of complex agrarian systems. This study presents a deep learning–based approach for the large‐scale, automated detection of ancient ...
Nazarij Buławka, Hector A. Orengo, Felipe Lumbreras Ruiz, Iban Berganzo‐Besga, Ekta Gupta   +4 more
wiley   +1 more source

Deep learning cone‐beam computed tomography image segmentation for the 3D visualization of mandibular infraosseous periodontal defects

Journal of Periodontology, EarlyView.
Abstract Background The accurate assessment of infraosseous periodontal defects is crucial for effective diagnosis and treatment planning. Cone‐beam computed tomography (CBCT) enables detailed imaging of these defects; however, to leverage their full potential, CBCT images must be reconstructed in 3 dimensions (3D).
Daniel Palkovics, Balint Molnar, Csaba Pinter, David García‐Mato, Andres Diaz‐Pinto, Attila Tanacs, Andrea Dobos, Peter Windisch, Christoph A. Ramseier   +8 more
wiley   +1 more source