Zobrazeno 1 - 10
of 50
pro vyhledávání: '"Haoji Hu"'
Autor:
Kuan Zhang, Haoji Hu, Kenneth Philbrick, Gian Marco Conte, Joseph D. Sobek, Pouria Rouzrokh, Bradley J. Erickson
Publikováno v:
Tomography, Vol 8, Iss 2, Pp 905-919 (2022)
There is a growing demand for high-resolution (HR) medical images for both clinical and research applications. Image quality is inevitably traded off with acquisition time, which in turn impacts patient comfort, examination costs, dose, and motion-in
Externí odkaz:
https://doaj.org/article/5bc8579661a94c42a3a6897b40467da4
Publikováno v:
Applied Sciences, Vol 13, Iss 20, p 11320 (2023)
Unmanned aerial vehicles (UAVs) have gained significant popularity across various domains, but their proliferation also raises concerns about security, public safety, and privacy. Consequently, the detection and tracking of UAVs have become crucial.
Externí odkaz:
https://doaj.org/article/5b5bcb52e8cd4393956f790e7fc44271
Publikováno v:
Remote Sensing, Vol 15, Iss 19, p 4732 (2023)
Forest tree species identification in the field of remote sensing has become an important research topic. Currently, few research methods combine global and local features, making it challenging to accurately handle the similarity between different c
Externí odkaz:
https://doaj.org/article/b4558f3ab04f4468bf11c59f8e22fbb2
Publikováno v:
Sensors, Vol 21, Iss 3, p 1018 (2021)
Emotion recognition is of great importance for artificial intelligence, robots, and medicine etc. Although many techniques have been developed for emotion recognition, with certain successes, they rely heavily on complicated and expensive equipment.
Externí odkaz:
https://doaj.org/article/1a685bdb67b441d5982f5869cd41f7cf
Autor:
Zuozhu Liu, Xiaoxuan He, Hualiang Wang, Huimin Xiong, Yan Zhang, Gaoang Wang, Jin Hao, Yang Feng, Fudong Zhu, Haoji Hu
Publikováno v:
IEEE Transactions on Medical Imaging. 42:467-480
Accurately delineating individual teeth and the gingiva in the three-dimension (3D) intraoral scanned (IOS) mesh data plays a pivotal role in many digital dental applications, e.g., orthodontics. Recent research shows that deep learning based methods
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4ad89aa2797b93f1ed90c3c84c240269
https://doi.org/10.1109/tmi.2022.3222388
https://doi.org/10.1109/tmi.2022.3222388
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:2450-2458
Existing image semantic segmentation methods favor learning consistent representations by extracting long-range contextual features with the attention, multi-scale, or graph aggregation strategies. These methods usually treat the misclassified and co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60f40500c6eb53bb1cdd44236cd94c26
https://doi.org/10.1609/aaai.v36i3.20145
https://doi.org/10.1609/aaai.v36i3.20145
Autor:
Xinyi Hu, Hangxiang Fang, Ling Zhang, Xue Zhang, Howard H. Yang, Dongxiao Yang, Bo Peng, Zheyang Li, Haoji Hu
Publikováno v:
Applied Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::745cc91e4d1b14b14c20b0b7cabfded9
https://doi.org/10.1007/s10489-023-04513-8
https://doi.org/10.1007/s10489-023-04513-8
Autor:
Xiner Zhu, Yichao Wu, Haoji Hu, Xianwei Zhuang, Jincao Yao, Di Ou, Wei Li, Mei Song, Na Feng, Dong Xu
Publikováno v:
Medical Physics. 49:3692-3704
Automatic segmentation of medical lesions is a prerequisite for efficient clinic analysis. Segmentation algorithms for multimodal medical images have received much attention in recent years. Different strategies for multimodal combination (or fusion)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::950ab79d26460f5f586a9a25a8450baf
https://doi.org/10.1002/mp.15610
https://doi.org/10.1002/mp.15610
Publikováno v:
Computer Vision – ACCV 2022 ISBN: 9783031263507
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82bb99b2ee06efba11f7acbaa7ced6b7
https://doi.org/10.1007/978-3-031-26351-4_16
https://doi.org/10.1007/978-3-031-26351-4_16
