Zobrazeno 1 - 10
of 306
pro vyhledávání: '"Zhang, Tianxiao"'
Vision Transformers have made remarkable progress in recent years, achieving state-of-the-art performance in most vision tasks. A key component of this success is due to the introduction of the Multi-Head Self-Attention (MHSA) module, which enables e
Externí odkaz:
http://arxiv.org/abs/2410.14874
3D point cloud classification requires distinct models from 2D image classification due to the divergent characteristics of the respective input data. While 3D point clouds are unstructured and sparse, 2D images are structured and dense. Bridging the
Externí odkaz:
http://arxiv.org/abs/2410.09691
The Vision Transformer (ViT) leverages the Transformer's encoder to capture global information by dividing images into patches and achieves superior performance across various computer vision tasks. However, the self-attention mechanism of ViT captur
Externí odkaz:
http://arxiv.org/abs/2407.19394
Autor:
Rahman, Raiyan, Indris, Christopher, Bramesfeld, Goetz, Zhang, Tianxiao, Li, Kaidong, Chen, Xiangyu, Grijalva, Ivan, McCornack, Brian, Flippo, Daniel, Sharda, Ajay, Wang, Guanghui
Aphid infestations are one of the primary causes of extensive damage to wheat and sorghum fields and are one of the most common vectors for plant viruses, resulting in significant agricultural yield losses. To address this problem, farmers often empl
Externí odkaz:
http://arxiv.org/abs/2405.04305
Autor:
Zhang, Tianxiao, Li, Kaidong, Chen, Xiangyu, Zhong, Cuncong, Luo, Bo, Grijalva, Ivan, McCornack, Brian, Flippo, Daniel, Sharda, Ajay, Wang, Guanghui
Aphid infestation poses a significant threat to crop production, rural communities, and global food security. While chemical pest control is crucial for maximizing yields, applying chemicals across entire fields is both environmentally unsustainable
Externí odkaz:
http://arxiv.org/abs/2308.05881
Autor:
Rahman, Raiyan, Indris, Christopher, Zhang, Tianxiao, Li, Kaidong, McCornack, Brian, Flippo, Daniel, Sharda, Ajay, Wang, Guanghui
Aphid infestations can cause extensive damage to wheat and sorghum fields and spread plant viruses, resulting in significant yield losses in agriculture. To address this issue, farmers often rely on chemical pesticides, which are inefficiently applie
Externí odkaz:
http://arxiv.org/abs/2307.10267
Autor:
Zhang, Tianxiao, Li, Kaidong, Chen, Xiangyu, Zhong, Cuncong, Luo, Bo, Teran, Ivan Grijalva, McCornack, Brian, Flippo, Daniel, Sharda, Ajay, Wang, Guanghui
Aphids are one of the main threats to crops, rural families, and global food security. Chemical pest control is a necessary component of crop production for maximizing yields, however, it is unnecessary to apply the chemical approaches to the entire
Externí odkaz:
http://arxiv.org/abs/2307.05929
Autor:
Zhang, Tianxiao, Bur, Andrés M., Kraft, Shannon, Kavookjian, Hannah, Renslo, Bryan, Chen, Xiangyu, Luo, Bo, Wang, Guanghui
Flexible laryngoscopy is commonly performed by otolaryngologists to detect laryngeal diseases and to recognize potentially malignant lesions. Recently, researchers have introduced machine learning techniques to facilitate automated diagnosis using la
Externí odkaz:
http://arxiv.org/abs/2305.16661
Publikováno v:
Journal of Imaging 2022, 8(7), 193
Label assignment plays a significant role in modern object detection models. Detection models may yield totally different performances with different label assignment strategies. For anchor-based detection models, the IoU (Intersection over Union) th
Externí odkaz:
http://arxiv.org/abs/2201.09396
Publikováno v:
Neurocomputing, Volume 475, 28 February 2022, Pages 102-111
In this paper, we propose a dual-module network architecture that employs a domain discriminative feature module to encourage the domain invariant feature module to learn more domain invariant features. The proposed architecture can be applied to any
Externí odkaz:
http://arxiv.org/abs/2112.15555