Zobrazeno 1 - 10
of 338
pro vyhledávání: '"Yang Xinquan"'
Autor:
Ruan, Zheng, Liu, Ruixuan, Chen, Shimin, Zhou, Mengying, Yang, Xinquan, Li, Wei, Chen, Chen, Shen, Wei
In the task of dense video captioning of Soccernet dataset, we propose to generate a video caption of each soccer action and locate the timestamp of the caption. Firstly, we apply Blip as our video caption framework to generate video captions. Then w
Externí odkaz:
http://arxiv.org/abs/2411.00882
Autor:
Cai, Zijian, Yang, Xinquan, Li, Xuguang, Luo, Xiaoling, Li, Xuechen, Shen, Linlin, Meng, He, Deng, Yongqiang
Panoramic X-ray is a simple and effective tool for diagnosing dental diseases in clinical practice. When deep learning models are developed to assist dentist in interpreting panoramic X-rays, most of their performance suffers from the limited annotat
Externí odkaz:
http://arxiv.org/abs/2406.13963
Autor:
Yang, Xinquan, Zhou, Guanqun, Sun, Wei, Zhang, Youjian, Wang, Zhongya, He, Jiahui, Zhang, Zhicheng
In computed tomography (CT), the presence of metallic implants in patients often leads to disruptive artifacts in the reconstructed images, hindering accurate diagnosis. Recently, a large amount of supervised deep learning-based approaches have been
Externí odkaz:
http://arxiv.org/abs/2406.12186
Autor:
Yang, Xinquan, Li, Xuguang, Luo, Xiaoling, Zeng, Leilei, Zhang, Yudi, Shen, Linlin, Deng, Yongqiang
Publikováno v:
MICCAI'2024
Surgical guide plate is an important tool for the dental implant surgery. However, the design process heavily relies on the dentist to manually simulate the implant angle and depth. When deep neural networks have been applied to assist the dentist qu
Externí odkaz:
http://arxiv.org/abs/2406.04603
Due to the poor prognosis of Pancreatic cancer, accurate early detection and segmentation are critical for improving treatment outcomes. However, pancreatic segmentation is challenged by blurred boundaries, high shape variability, and class imbalance
Externí odkaz:
http://arxiv.org/abs/2312.15859
Autor:
Cioppa, Anthony, Giancola, Silvio, Somers, Vladimir, Magera, Floriane, Zhou, Xin, Mkhallati, Hassan, Deliège, Adrien, Held, Jan, Hinojosa, Carlos, Mansourian, Amir M., Miralles, Pierre, Barnich, Olivier, De Vleeschouwer, Christophe, Alahi, Alexandre, Ghanem, Bernard, Van Droogenbroeck, Marc, Kamal, Abdullah, Maglo, Adrien, Clapés, Albert, Abdelaziz, Amr, Xarles, Artur, Orcesi, Astrid, Scott, Atom, Liu, Bin, Lim, Byoungkwon, Chen, Chen, Deuser, Fabian, Yan, Feng, Yu, Fufu, Shitrit, Gal, Wang, Guanshuo, Choi, Gyusik, Kim, Hankyul, Guo, Hao, Fahrudin, Hasby, Koguchi, Hidenari, Ardö, Håkan, Salah, Ibrahim, Yerushalmy, Ido, Muhammad, Iftikar, Uchida, Ikuma, Be'ery, Ishay, Rabarisoa, Jaonary, Lee, Jeongae, Fu, Jiajun, Yin, Jianqin, Xu, Jinghang, Nang, Jongho, Denize, Julien, Li, Junjie, Zhang, Junpei, Kim, Juntae, Synowiec, Kamil, Kobayashi, Kenji, Zhang, Kexin, Habel, Konrad, Nakajima, Kota, Jiao, Licheng, Ma, Lin, Wang, Lizhi, Wang, Luping, Li, Menglong, Zhou, Mengying, Nasr, Mohamed, Abdelwahed, Mohamed, Liashuha, Mykola, Falaleev, Nikolay, Oswald, Norbert, Jia, Qiong, Pham, Quoc-Cuong, Song, Ran, Hérault, Romain, Peng, Rui, Chen, Ruilong, Liu, Ruixuan, Baikulov, Ruslan, Fukushima, Ryuto, Escalera, Sergio, Lee, Seungcheon, Chen, Shimin, Ding, Shouhong, Someya, Taiga, Moeslund, Thomas B., Li, Tianjiao, Shen, Wei, Zhang, Wei, Li, Wei, Dai, Wei, Luo, Weixin, Zhao, Wending, Zhang, Wenjie, Yang, Xinquan, Ma, Yanbiao, Joo, Yeeun, Zeng, Yingsen, Gan, Yiyang, Zhu, Yongqiang, Zhong, Yujie, Ruan, Zheng, Li, Zhiheng, Huang, Zhijian, Meng, Ziyu
The SoccerNet 2023 challenges were the third annual video understanding challenges organized by the SoccerNet team. For this third edition, the challenges were composed of seven vision-based tasks split into three main themes. The first theme, broadc
Externí odkaz:
http://arxiv.org/abs/2309.06006
TCSloT: Text Guided 3D Context and Slope Aware Triple Network for Dental Implant Position Prediction
In implant prosthesis treatment, the surgical guide of implant is used to ensure accurate implantation. However, such design heavily relies on the manual location of the implant position. When deep neural network has been proposed to assist the denti
Externí odkaz:
http://arxiv.org/abs/2308.05355
Autor:
Yang, Xinquan, Xie, Jinheng, Li, Xuguang, Li, Xuechen, Li, Xin, Shen, Linlin, Deng, Yongqiang
When deep neural network has been proposed to assist the dentist in designing the location of dental implant, most of them are targeting simple cases where only one missing tooth is available. As a result, literature works do not work well when there
Externí odkaz:
http://arxiv.org/abs/2306.14406
Autor:
Yang, Xinquan, Li, Xuguang, Li, Xuechen, Chen, Wenting, Shen, Linlin, Li, Xin, Deng, Yongqiang
Publikováno v:
Expert Systems With Applications 2023
In implant prosthesis treatment, the design of the surgical guide heavily relies on the manual location of the implant position, which is subjective and prone to doctor's experiences. When deep learning based methods has started to be applied to addr
Externí odkaz:
http://arxiv.org/abs/2305.10044
Publikováno v:
Neural Computing and Applications 2024
Implant prosthesis is the most appropriate treatment for dentition defect or dentition loss, which usually involves a surgical guide design process to decide the implant position. However, such design heavily relies on the subjective experiences of d
Externí odkaz:
http://arxiv.org/abs/2210.16467