Results 131 to 140 of about 14,679 (231)

Multiscale transformer-based network for rangeland plant classification used in pasture scoring [PDF]

Rangeland ecosystems have been sources for pastoral communities. However, traditional seasonal mobility patterns are disrupted by climate change, requiring more dynamic, data-driven plant-based rangeland assessment.
Nasirahmadi, Abozar
core  

Weakly Supervised Intracranial Hemorrhage Segmentation using Head-Wise Gradient-Infused Self-Attention Maps from a Swin Transformer in Categorical Learning

, 2023
Intracranial hemorrhage (ICH) is a life-threatening medical emergency caused by various factors. Timely and precise diagnosis of ICH is crucial for administering effective treatment and improving patient survival rates.
Rasoulian, Amirhossein, Salari, Soorena, Xiao, Yiming   +2 more
core  

B-Cos Aligned Transformers Learn Human-Interpretable Features

Vision Transformers (ViTs) and Swin Transformers (Swin) are currently state-of-the-art in computational pathology. However, domain experts are still reluctant to use these models due to their lack of interpretability.
Boxberg, Melanie, Cid, Yashin Dicente, Klaiman, Eldad, Lahiani, Amal, Lienemann, Peter, Matek, Christian, Peng, Tingying, Theis, Fabian J., Tran, Manuel, Wagner, Sophia J.   +9 more
core  

Deep Reinforcement Learning with Swin Transformers

Proceedings of the 2024 8th International Conference on Digital Signal Processing
Transformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks. Meanwhile, there have been efforts to adapt transformers to visual tasks of machine learning, including Vision Transformers and Swin Transformers.
Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad   +3 more
openaire   +2 more sources

Vision Transformer Adapters for Generalizable Multitask Learning

, 2023
We introduce the first multitasking vision transformer adapters that learn generalizable task affinities which can be applied to novel tasks and domains.
Bhattacharjee, Deblina, Salzmann, Mathieu, Süsstrunk, Sabine   +2 more
core  

An enhanced Swin Transformer for soccer player reidentification

Scientific Reports
AbstractThe re-identification (ReID) of objects in images is a widely studied topic in computer vision, with significant relevance to various applications. The ReID of players in broadcast videos of team sports is the focus of this study. We specifically focus on identifying the same player in images taken at any given moment during a game from various
Akan, Sara, VARLI, Songül, Bhuiyan, Mohammad Alfrad Nobel   +2 more
openaire   +4 more sources

Fast Aerodynamic Prediction of Airfoil with Trailing Edge Flap Based on Multi-Task Deep Learning

Aerospace
Conventional methods for solving Navier–Stokes (NS) equations to analyze flow fields and aerodynamic forces of airfoils with trailing edge flaps (TEFs) are known for their significant time cost.
Chi Zhang, Zhiyuan Hu, Yongjie Shi, Guohua Xu   +3 more
doaj   +1 more source

The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification

Algorithms
The accurate detection and classification of pavement damage are critical for ensuring timely maintenance and extending the service life of road infrastructure.
Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang   +4 more
doaj   +1 more source

Seismic Interpolation Transformer for Consecutively Missing Data: A Case Study in DAS-VSP Data

Distributed optical fiber acoustic sensing (DAS) is a rapidly-developed seismic acquisition technology with advantages of low cost, high resolution, high sensitivity, and small interval, etc.
Cheng, Ming, Dong, Xintong, Lin, Jun, Lu, Shaoping, Zhong, Tie   +4 more
core  

Patched-Based Swin Transformer Hyperprior for Learned Image Compression. [PDF]

J Imaging
Buthelezi SB, Tapamo JR.
europepmc   +1 more source