Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Sehwan Ki"'
Publikováno v:
IEEE Access, Vol 8, Pp 228605-228618 (2020)
The final consumer of videos is mostly human. Therefore, if videos can be compressed by fully utilizing the perception characteristics of human visual systems (HVS), the bitrates of the compressed videos can be significantly reduced with subjective v
Externí odkaz:
https://doaj.org/article/147ba642c8814654ad405a1b81c1e3d1
Publikováno v:
International Neurourology Journal, Vol 28, Iss 1, Pp 4-10 (2024)
Urinary tract infections (UTIs) are among the most common bacterial infections worldwide and are particularly prevalent in women. Recurrent UTIs significantly diminish quality of life due to their symptoms and frequent relapses. Patients often experi
Externí odkaz:
https://doaj.org/article/17b8642e89fe4d4d9f54ab7d23cd73e8
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 17087-17098 (2024)
Multilabel remote sensing image classification is a fundamental task that classifies multiple objects and land covers within an image. However, training deep learning models for this task requires a considerable cost of labeling. While several effort
Externí odkaz:
https://doaj.org/article/98979b5b0c4e4d888b359e50dc8f6587
Publikováno v:
IEEE Transactions on Image Processing. 27:3178-3193
Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attem
Recently, due to the strength of deep convolutional neural networks (CNN), many CNN-based image quality assessment (IQA) models have been studied. However, previous CNN-based IQA models likely have yet to utilize the characteristics of the human visu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::465d5c2717d980859a944e7b6c548411
Publikováno v:
International Neurourology Journal, Vol 27, Iss Suppl 2, Pp S82-90 (2023)
Purpose The development of optics-based wearables for bladder volume monitoring has emerged as a significant topic in recent years. Given the innovative nature of this technology, there is currently no bladder phantom available to effectively validat
Externí odkaz:
https://doaj.org/article/09d211f0bbbb4d8881e4a2f437ce9398
Publikováno v:
CVPR Workshops
Haze removal is one of the essential image enhancement processes that makes degraded images visually pleasing. Since haze in images often appears differently depending on the surroundings, haze removal requires the use of spatial information to effec
Publikováno v:
CVPR Workshops
A receptive field is defined as the region in an input image space that an output image pixel is looking at. Thus, the receptive field size influences the learning of deep convolution neural networks. Especially, in single image dehazing problems, la
Autor:
Cosmin Ancuti, Ruhao Zhao, Xiaoping Ma, Yong Qin, Limin Jia, Klaus Friedel, Sehwan Ki, Hyeonjun Sim, Jae-Seok Choi, Sooye Kim, Soomin Seo, Codruta O. Ancuti, Saehun Kim, Munchurl Kim, Ranjan Mondal, Sanchayan Santra, Bhabatosh Chanda, Jinlin Liu, Kangfu Mei, Juncheng Li, null Luyao, Faming Fang, Radu Timofte, Aiwen Jiang, Xiaochao Qu, Ting Liu, Pengfei Wang, Biao Sun, Jiangfan Deng, Yuhang Zhao, Ming Hong, Jingying Huang, Yizhi Chen, Luc Van Gool, Erin Chen, Xiaoli Yu, Tingting Wu, Anil Genc, Deniz Engin, Hazim Kemal Ekenel, Wenzhe Liu, Tong Tong, Gen Li, Qinquan Gao, Lei Zhang, Zhan Li, Daofa Tang, Yuling Chen, Ziying Huo, Aitor Alvarez-Gila, Adrian Galdran, Alessandro Bria, Javier Vazquez-Corral, Marcelo Bertalmo, H. Seckin Demir, Ming-Hsuan Yang, Omer Faruk Adil, Huynh Xuan Phung, Xin Jin, Jiale Chen, Chaowei Shan, Zhibo Chen, Vishal M. Patel, He Zhang, Vishwanath A. Sindagi
Publikováno v:
CVPR Workshops
This paper reviews the first challenge on image dehazing (restoration of rich details in hazy image) with focus on proposed solutions and results. The challenge had 2 tracks. Track 1 employed the indoor images (using I-HAZE dataset), while Track 2 ou
Autor:
Radu Timofte, Shuhang Gu, Jiqing Wu, Luc Van Gool, Lei Zhang, Ming-Hsuan Yang, Muhammad Haris, Greg Shakhnarovich, Norimichi Ukita, Shijia Hu, Yijie Bei, Zheng Hui, Xiao Jiang, Yanan Gu, Jie Liu, Yifan Wang, Federico Perazzi, Brian McWilliams, Alexander Sorkine-Hornung, Olga Sorkine-Hornung, Christopher Schroers, Jiahui Yu, Yuchen Fan, Jianchao Yang, Ning Xu, Zhaowen Wang, Xinchao Wang, Thomas S. Huang, Xintao Wang, Ke Yu, Tak-Wai Hui, Chao Dong, Liang Lin, Chen Change Loy, Dongwon Park, Kwanyoung Kim, Se Young Chun, Kai Zhang, Pengjv Liu, Wangmeng Zuo, Shi Guo, Jiye Liu, Jinchang Xu, Yijiao Liu, Fengye Xiong, Yuan Dong, Hongliang Bai, Alexandru Damian, Nikhil Ravi, Sachit Menon, Cynthia Rudin, Junghoon Seo, Taegyun Jeon, Jamyoung Koo, Seunghyun Jeon, Soo Ye Kim, Jae-Seok Choi, Sehwan Ki, Soomin Seo, Hyeonjun Sim, Saehun Kim, Munchurl Kim, Rong Chen, Kun Zeng, Jinkang Guo, Yanyun Qu, Cuihua Li, Namhyuk Ahn, Byungkon Kang, Kyung-Ah Sohn, Yuan Yuan, Jiawei Zhang, Jiahao Pang, Xiangyu Xu, Yan Zhao, Wei Deng, Sibt Ul Hussain, Muneeb Aadil, Rafia Rahim, Xiaowang Cai, Fang Huang, Yueshu Xu, Pablo Navarrete Michelini, Dan Zhu, Hanwen Liu, Jun-Hyuk Kim, Jong-Seok Lee, Yiwen Huang, Ming Qiu, Liting Jing, Jiehang Zeng, Ying Wang, Manoj Sharma, Rudrabha Mukhopadhyay, Avinash Upadhyay, Sriharsha Koundinya, Ankit Shukla, Santanu Chaudhury, Zhe Zhang, Yu Hen Hu, Lingzhi Fu
Publikováno v:
CVPR Workshops
This paper reviews the 2nd NTIRE challenge on single image super-resolution (restoration of rich details in a low resolution image) with focus on proposed solutions and results. The challenge had 4 tracks. Track 1 employed the standard bicubic downsc