Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Li, Huixia"'
Autor:
Li, Jiashi, Xia, Xin, Li, Wei, Li, Huixia, Wang, Xing, Xiao, Xuefeng, Wang, Rui, Zheng, Min, Pan, Xin
Due to the complex attention mechanisms and model design, most existing vision Transformers (ViTs) can not perform as efficiently as convolutional neural networks (CNNs) in realistic industrial deployment scenarios, e.g. TensorRT and CoreML. This pos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fc77d9a8c990f3a4ca7df16852501357
We present an event-by-event study of photon production in the early stage of high energy nuclear collisions, where the system is dominant by highly occupied of gluons. The photons are produced through the gluon fusion and splitting processes when st
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a46eed6175b6b025df076b3692d7b621
Autor:
Li, Huixia, Yan, Chenqian, Lin, Shaohui, Zheng, Xiawu, Li, Yuchao, Zhang, Baochang, Yang, Fan, Ji, Rongrong
Deep convolutional neural networks (DCNNs) have shown dominant performance in the task of super-resolution (SR). However, their heavy memory cost and computation overhead significantly restrict their practical deployments on resource-limited devices,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d770d9df0f63e075c01ab71dd25d8581