Zobrazeno 1 - 10
of 756
pro vyhledávání: '"Zhou Junlin"'
Publikováno v:
E3S Web of Conferences, Vol 341, p 01022 (2022)
Electric Power data has the characteristics of strong real-time, fine granularity and high accuracy. It can more accurately reflect the current industrial structure and is suitable for the monitoring of high-quality economic development. In order to
Externí odkaz:
https://doaj.org/article/3fdc054eb35c467ca4c308534698b7cd
Autor:
Zha, Liangyu, Zhou, Junlin, Li, Liyao, Wang, Rui, Huang, Qingyi, Yang, Saisai, Yuan, Jing, Su, Changbao, Li, Xiang, Su, Aofeng, Zhang, Tao, Zhou, Chen, Shou, Kaizhe, Wang, Miao, Zhu, Wufang, Lu, Guoshan, Ye, Chao, Ye, Yali, Ye, Wentao, Zhang, Yiming, Deng, Xinglong, Xu, Jie, Wang, Haobo, Chen, Gang, Zhao, Junbo
Tables are prevalent in real-world databases, requiring significant time and effort for humans to analyze and manipulate. The advancements in large language models (LLMs) have made it possible to interact with tables using natural language input, bri
Externí odkaz:
http://arxiv.org/abs/2307.08674
Autor:
Deng, Yan1 (AUTHOR) 18121927870@163.com, Zhou, Junlin1 (AUTHOR) 18282097686@163.com, Wang, Bixia1 (AUTHOR) 13684327650@163.com, Xu, Xiao1 (AUTHOR) wangbixia@cwnu.edu.cn, Huang, Tingyu1 (AUTHOR), Xu, Zhou2 (AUTHOR) xzhbiol@163.com, Zhao, Chunyan3 (AUTHOR) 17883305560@163.com
Publikováno v:
Molecules. Sep2024, Vol. 29 Issue 17, p4219. 18p.
Autor:
Guyatt, Gordon, Petrisor, Brad, Thabane, Lehana, Boniface, Respicious, Browner, Bruce, Pollak, Andrew, Slobogean, Gerard, Schemitsch, Emil, McKay, Paula, Tai, Kerry, Heels-Ansdell, Diane, Buckingham, Lisa, Norton, Robyn, Zhang, Jing, Parveen, Samina, Bhaumik, Soumyadeep, Morshed, Saam, Mackechnie, Madeline C., Zhang, Zhentao, Ma, Yinghua, Qin, Yanguo, Hu, Sanbao, Qi, Baochang, Dai, Wenjie, Cai, Xinyu, Rui, Gang, Chen, Hua, Shetty, Vijay, Dumbre Patil, Sampat, Patil, Sanjay, Shrivastava, Sandeep, Mittal, Ravi, Jepegnanam, Thilak Samuel, Mahajan, Anupam, Chhabra, Harvinder Singh, N, Rajagopalan, Amaravathi, Rajkumar S., Dhillon, Mandeep S., Chase, Asolie, Bhavsar, Neel M., Saadat, Soheil, Byanjankar, Subin, Qadir, Raja Irfan, Tabu, Irewin Alagar, Ponggsamakthai, Wanjak, Sa-ngasoongsong, Paphon, Subramanian, Panchu, Ndeleva, Benjamin Muluku, Lutomia, Mark, Otseyeno, Fred Mathew Toboso, Mwangi, Geoffrey Chege, Ndasi, Henry Tanyi, Konadu-Yeboah, Dominic, Firth, Gregory, Marealle, Paul, Temu, Rogers, Mutanda, Tony, Rio, Marcelo, Quintero, Jose Eduardo, Zuluaga, Mauricio, Minueza, Tomás, Madrigal, Ricardo, Ylizaliturri, Manuel, Garuz, Mario, Segovia Altieri, Julio, Escalante Elguezabal, Igor A., Armstrong, Elizabeth, Rogers, Kris, Li, Chuan Silvia, Jagnoor, Jagnoor, Moroz, Paul, Oguzie, Gerald Chukwuemeka, Hailu, Samuel, Miclau, Theodore, III, de la Huerta, Fernando, Martinez-Ruiz, Jose de Jesus, Bidolegui, Fernando, Zhou, Junlin, Ma, Xinlong, Wu, Bo, Sancheti, Parag, Quang, La Ngoc, Baigi, Vali, Haddadi, Mashyaneh, Tian, Maoyi, Sprague, Sheila, Devereaux, P J, Bhandari, Mohit, Ivers, Rebecca *
Publikováno v:
In The Lancet Healthy Longevity August 2024 5(8):e552-e562
Autor:
Liu, Suwei, Pan, Haojie, Li, Shenglin, Li, Zhengxiao, Sun, Jiachen, Ren, Tiezhu, Zhou, Junlin
Publikováno v:
In Journal of Bone Oncology August 2024 47
Publikováno v:
In Marine and Petroleum Geology July 2024 165
Autor:
Jing, Mengyuan, Xi, Huaze, Li, Jianying, Liu, Qing, Zhu, Hao, Sun, Qiu, Zhang, Yuting, Liu, Xuehui, Ren, Wei, Zhang, Bin, Deng, Liangna, Han, Tao, Zhou, Junlin
Publikováno v:
In Clinical Imaging October 2024 114
Autor:
Deng, Liangna, Yang, Jingjing, Zhang, Mingtao, Zhu, Kaibo, Zhang, Junfu, Ren, Wei, Zhang, Yuting, Jing, Mengyuan, Han, Tao, Zhang, Bin, Zhou, Junlin
Publikováno v:
In European Journal of Radiology October 2024 179
Autor:
Gao, Yuling, Liu, Yang, Zhao, Yanrui, Shan, Lei, Wang, Hanzhou, Xu, Xiaopei, Zhao, Binzhi, Zhou, Junlin
Publikováno v:
In Foot and Ankle Surgery October 2024 30(7):594-602
Channel pruning is a promising technique to compress the parameters of deep convolutional neural networks(DCNN) and to speed up the inference. This paper aims to address the long-standing inefficiency of channel pruning. Most channel pruning methods
Externí odkaz:
http://arxiv.org/abs/2108.13728