The Ninth NTIRE 2024 Efficient Super-Resolution Challenge Report

Autor: Ren, Bin, Li, Yawei, Mehta, Nancy, Timofte, Radu, Yu, Hongyuan, Wan, Cheng, Hong, Yuxin, Han, Bingnan, Wu, Zhuoyuan, Zou, Yajun, Liu, Yuqing, Li, Jizhe, He, Keji, Fan, Chao, Zhang, Heng, Zhang, Xiaolin, Yin, Xuanwu, Zuo, Kunlong, Liao, Bohao, Xia, Peizhe, Peng, Long, Du, Zhibo, Di, Xin, Li, Wangkai, Wang, Yang, Zhai, Wei, Pei, Renjing, Guo, Jiaming, Xu, Songcen, Cao, Yang, Zha, Zhengjun, Wang, Yan, Liu, Yi, Wang, Qing, Zhang, Gang, Zhang, Liou, Zhao, Shijie, Sun, Long, Pan, Jinshan, Dong, Jiangxin, Tang, Jinhui, Liu, Xin, Yan, Min, Wang, Qian, Zhou, Menghan, Yan, Yiqiang, Liu, Yixuan, Chan, Wensong, Tang, Dehua, Zhou, Dong, Wang, Li, Tian, Lu, Emad, Barsoum, Jia, Bohan, Qiao, Junbo, Zhou, Yunshuai, Zhang, Yun, Li, Wei, Lin, Shaohui, Zhou, Shenglong, Chen, Binbin, Liao, Jincheng, Zhao, Suiyi, Zhang, Zhao, Wang, Bo, Luo, Yan, Wei, Yanyan, Li, Feng, Wang, Mingshen, Guan, Jinhan, Hu, Dehua, Yu, Jiawei, Xu, Qisheng, Sun, Tao, Lan, Long, Xu, Kele, Lin, Xin, Yue, Jingtong, Yang, Lehan, Du, Shiyi, Qi, Lu, Ren, Chao, Han, Zeyu, Wang, Yuhan, Chen, Chaolin, Li, Haobo, Zheng, Mingjun, Yang, Zhongbao, Song, Lianhong, Yan, Xingzhuo, Fu, Minghan, Zhang, Jingyi, Li, Baiang, Zhu, Qi, Xu, Xiaogang, Guo, Dan, Guo, Chunle, Chen, Jiadi, Long, Huanhuan, Duanmu, Chunjiang, Lei, Xiaoyan, Liu, Jie, Jia, Weilin, Cao, Weifeng, Zhang, Wenlong, Mao, Yanyu, Guo, Ruilong, Zhang, Nihao, Pandey, Manoj, Chernozhukov, Maksym, Le, Giang, Cheng, Shuli, Wang, Hongyuan, Wei, Ziyan, Tang, Qingting, Wang, Liejun, Li, Yongming, Guo, Yanhui, Xu, Hao, Khatami-Rizi, Akram, Mahmoudi-Aznaveh, Ahmad, Hsu, Chih-Chung, Lee, Chia-Ming, Chou, Yi-Shiuan, Joshi, Amogh, Akalwadi, Nikhil, Malagi, Sampada, Yashaswini, Palani, Desai, Chaitra, Tabib, Ramesh Ashok, Patil, Ujwala, Mudenagudi, Uma

This paper provides a comprehensive review of the NTIRE 2024 challenge, focusing on efficient single-image super-resolution (ESR) solutions and their outcomes. The task of this challenge is to super-resolve an input image with a magnification factor

Externí odkaz: http://arxiv.org/abs/2404.10343

A Fast and Robust Range Alignment Method for ISAR Imaging Based on a Deep Learning Network and Regional Multi-Scale Minimum Entropy Method.

Autor: Ning, Qianhao¹ (AUTHOR) 19b921012@stu.hit.edu.cn, Wang, Hongyuan¹ (AUTHOR), Yan, Zhiqiang¹ (AUTHOR) yanzhiqiang@hit.edu.cn, Wang, Zijian¹ (AUTHOR), Lu, Yinxi¹ (AUTHOR)

Publikováno v: Remote Sensing. Oct2024, Vol. 16 Issue 19, p3677. 15p.

SHREC'22 Track: Sketch-Based 3D Shape Retrieval in the Wild

Autor: Qin, Jie, Yuan, Shuaihang, Chen, Jiaxin, Amor, Boulbaba Ben, Fang, Yi, Hoang-Xuan, Nhat, Chu, Chi-Bien, Nguyen-Ngoc, Khoi-Nguyen, Cao, Thien-Tri, Ngo, Nhat-Khang, Huynh, Tuan-Luc, Nguyen, Hai-Dang, Tran, Minh-Triet, Luo, Haoyang, Wang, Jianning, Zhang, Zheng, Xin, Zihao, Wang, Yang, Wang, Feng, Tang, Ying, Chen, Haiqin, Wang, Yan, Zhou, Qunying, Zhang, Ji, Wang, Hongyuan

Sketch-based 3D shape retrieval (SBSR) is an important yet challenging task, which has drawn more and more attention in recent years. Existing approaches address the problem in a restricted setting, without appropriately simulating real application s

Externí odkaz: http://arxiv.org/abs/2207.04945

A modified model of PANoptosisto identify prognosis and immunotherapy response in bladder cancer

Autor: Lv, Weichao, Lei, Xiaohang, Wang, Hongyuan, Wang, Tongtong, Zhang, Jianguo

Publikováno v: In International Journal of Biochemistry and Cell Biology November 2024 176

Gut microbiota-bile acid crosstalk contributes to intestinal damage after nitrate exposure in Bufo gargarizans tadpoles

Autor: Liu, Ying, Wang, Yaxi, Wei, Fei, Chai, Lihong, Wang, Hongyuan

Publikováno v: In Science of the Total Environment 15 September 2024 943