DARK: Denoising, Amplification, Restoration Kit

Autor: Li, Zhuoheng, Pan, Yuheng, Yu, Houcheng, Zhang, Zhiheng

This paper introduces a novel lightweight computational framework for enhancing images under low-light conditions, utilizing advanced machine learning and convolutional neural networks (CNNs). Traditional enhancement techniques often fail to adequate

Externí odkaz: http://arxiv.org/abs/2405.12891

tRF-Gly-GCC in Atretic Follicles Promotes Ferroptosis in Granulosa Cells by Down-Regulating MAPK1.

Autor: Pan, Yuheng^1,2,3 (AUTHOR) panyuheng@stu.sicau.edu.cn, Gan, Mailin^1,2,3 (AUTHOR) ganmailin@sicau.edu.cn, Wu, Shuang^1,2,3 (AUTHOR) wushuang@stu.sicau.edu.cn, He, Yuxu^1,2,3 (AUTHOR) heyuxu@stu.sicau.edu.cn, Feng, Jinkang^1,2,3 (AUTHOR) fengjinkang@stu.sicau.edu.cn, Jing, Yunhong^1,2,3 (AUTHOR) jingyunhong@stu.sicau.edu.cn, Li, Jiaxin^1,2,3 (AUTHOR) lijiaxin1@stu.sicau.edu.cn, Chen, Qian^1,2,3 (AUTHOR) chenqian1@stu.sicau.edu.cn, Tong, Jiang^1,2,3 (AUTHOR) 202100216@stu.sicau.edu.cn, Kang, Lingfan^1,2,3 (AUTHOR) kanglingfan@stu.sicau.edu.cn, Chen, Lei^1,2,3 (AUTHOR) chenlei815918@sicau.edu.cn, Zhao, Ye^1,2,3 (AUTHOR) zhye@sicau.edu.cn, Niu, Lili^1,2,3 (AUTHOR) niulili@sicau.edu.cn, Zhang, Shunhua^1,2,3 (AUTHOR) 14081@sicau.edu.cn, Wang, Yan^1,2,3 (AUTHOR) wangyan2023@sicau.edu.cn, Zhu, Li^1,2,3 (AUTHOR) zhuli@sicau.edu.cn, Shen, Linyuan^1,2,3 (AUTHOR) zhuli@sicau.edu.cn

Publikováno v: International Journal of Molecular Sciences. Aug2024, Vol. 25 Issue 16, p9061. 15p.

SP: Modelling and Simulation of Software-Defined Smart Park Network based on Controller Fault Recovery

Autor: Li, Guoyan, Cui, Wentao, Liu, Shudong, Pan, Yuheng

Publikováno v: In Simulation Modelling Practice and Theory December 2023 129

Dynamic Path Planning of Vehicles Based on the Adaptive Potential Field and Hierarchical Replacement Immune Algorithm.

Autor: Pan, Yuheng, Tao, Yixin, Lu, Weijia, Li, Guoyan, Cong, Jia

Publikováno v: Arabian Journal for Science & Engineering (Springer Science & Business Media B.V. ); Sep2024, Vol. 49 Issue 9, p12113-12129, 17p

ATG-PVD:Ticketing Parking Violations on a Drone

Autor: Wang, Hengli, Liu, Yuxuan, Huang, Huaiyang, Pan, Yuheng, Yu, Wenbin, Jiang, Jialin, Lyu, Dianbin, Bocus, Mohammud J., Liu, Ming, Pitas, Ioannis, Fan, Rui

Publikováno v: Wang, H, Liu, Y, Huang, H, Pan, Y, Yu, W, Jiang, J, Lyu, D, Bocus, M J, Liu, M, Pitas, I & Fan, R 2021, ATG-PVD : Ticketing Parking Violations on a Drone . in A Bartoli & A Fusiello (eds), Computer Vision--ECCV 2020 Workshops . Lecture Notes in Computer Science, vol. 12538, Springer International Publishing AG, pp. 541-557, Computer Vision – ECCV 2020 Workshops, Glasgow, United Kingdom, 23/08/20 . https://doi.org/10.1007/978-3-030-66823-5_32

In this paper, we introduce a novel suspect-and-investigate framework, which can be easily embedded in a drone for automated parking violation detection (PVD). Our proposed framework consists of: 1) SwiftFlow, an efficient and accurate convolutional

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2642::7e3d3c1a6632848d8538435dc2e9de0a
https://hdl.handle.net/1983/f036c83d-078b-4950-8015-ffefdfd9292b