Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Wu, Binghong"'
Autor:
Lu, Jinghui, Yu, Haiyang, Wang, Yanjie, Ye, Yongjie, Tang, Jingqun, Yang, Ziwei, Wu, Binghong, Liu, Qi, Feng, Hao, Wang, Han, Liu, Hao, Huang, Can
Recently, many studies have demonstrated that exclusively incorporating OCR-derived text and spatial layouts with large language models (LLMs) can be highly effective for document understanding tasks. However, existing methods that integrate spatial
Externí odkaz:
http://arxiv.org/abs/2407.01976
Autor:
Zhao, Weichao, Feng, Hao, Liu, Qi, Tang, Jingqun, Wei, Shu, Wu, Binghong, Liao, Lei, Ye, Yongjie, Liu, Hao, Li, Houqiang, Huang, Can
Tables contain factual and quantitative data accompanied by various structures and contents that pose challenges for machine comprehension. Previous methods generally design task-specific architectures and objectives for individual tasks, resulting i
Externí odkaz:
http://arxiv.org/abs/2406.01326
Autor:
Tang, Jingqun, Lin, Chunhui, Zhao, Zhen, Wei, Shu, Wu, Binghong, Liu, Qi, Feng, Hao, Li, Yang, Wang, Siqi, Liao, Lei, Shi, Wei, Liu, Yuliang, Liu, Hao, Xie, Yuan, Bai, Xiang, Huang, Can
Text-centric visual question answering (VQA) has made great strides with the development of Multimodal Large Language Models (MLLMs), yet open-source models still fall short of leading models like GPT4V and Gemini, partly due to a lack of extensive,
Externí odkaz:
http://arxiv.org/abs/2404.12803
Autor:
Zhao, Zhen, Tang, Jingqun, Lin, Chunhui, Wu, Binghong, Huang, Can, Liu, Hao, Tan, Xin, Zhang, Zhizhong, Xie, Yuan
Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straightforward solution is performing model fine-tuning tailored to a specific scenario, but it
Externí odkaz:
http://arxiv.org/abs/2311.13120
Autor:
Zhou, Wenshuo, Yang, Dalu, Wu, Binghong, Yang, Yehui, Wu, Junde, Wang, Xiaorong, Wang, Lei, Huang, Haifeng, Xu, Yanwu
Deep learning based medical imaging classification models usually suffer from the domain shift problem, where the classification performance drops when training data and real-world data differ in imaging equipment manufacturer, image acquisition prot
Externí odkaz:
http://arxiv.org/abs/2205.15658
Autor:
Wu, Binghong, Yang, Yehui, Yang, Dalu, Wu, Junde, Wang, Xiaorong, Huang, Haifeng, Wang, Lei, Xu, Yanwu
In object detection, multi-level prediction (e.g., FPN) and reweighting skills (e.g., focal loss) have drastically improved one-stage detector performance. However, the synergy between these two techniques is not fully explored in a unified framework
Externí odkaz:
http://arxiv.org/abs/2109.07217
Autor:
Mosisa, Mengistu Tadesse, Zhang, Pengkun, Wu, Binghong, Chen, Longyan, Su, Zhengjie, Li, Ping, Zhang, Hanya, Farooq, Ambar, Huang, Ting, Abdeta, Adugna Boke, Zelekew, Osman Ahmed, Kuo, Dong-Hau, Lin, Jinguo, Chen, Xiaoyun, Lu, Dongfang
Publikováno v:
In Journal of Environmental Chemical Engineering October 2024 12(5)
Autor:
Mosisa, Mengistu Tadesse, Zhang, Pengkun, Su, Zhengjie, Wu, Binghong, Chen, Longyan, Liao, Yiqiang, Farooq, Ambar, Lu, Dongfang, Abdeta, Adugna Boke, Kuo, Dong-Hau, Lin, Jinguo, Chen, Xiaoyun
Publikováno v:
In Journal of Environmental Chemical Engineering April 2024 12(2)
Autor:
Su, Zhengjie, Wu, Binghong, Chen, Longyan, Mosisa, Mengistu Tadesse, Zhang, Pengkun, Wu, Qinhan, Kuo, Dong-Hau, Lu, Dongfang, Zelekew, Osman Ahmed, Lin, Jinguo, Chen, Xiaoyun
Publikováno v:
In Journal of Science: Advanced Materials and Devices December 2023 8(4)
Autor:
Yang, Yehui, Shang, Fangxin, Wu, Binghong, Yang, Dalu, Wang, Lei, Xu, Yanwu, Zhang, Wensheng, Zhang, Tianzhu
Diabetic retinopathy (DR) grading from fundus images has attracted increasing interest in both academic and industrial communities. Most convolutional neural network (CNN) based algorithms treat DR grading as a classification task via image-level ann
Externí odkaz:
http://arxiv.org/abs/2008.00610