no code implementations • ICML 2020 • Liu Liu, Lei Deng, Zhaodong Chen, yuke wang, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie
Using Deep Neural Networks (DNNs) in machine learning tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements and energy constraints because of the memory-bound and the compute-bound execution pattern of DNNs.
1 code implementation • 28 Jun 2022 • Jiewen Xiao, Wenbin Liao, Ming Zhang, Jing Wang, Jianxin Wang, Yihua Yang
Molecular and morphological characters, as important parts of biological taxonomy, are contradictory but need to be integrated.
no code implementations • 27 Jun 2022 • Wenbin Liao, Jiewen Xiao, Chengbo Zhao, Yonggong Han, ZhiJie Geng, Jianxin Wang, Yihua Yang
In this paper, we propose a new model based on attention-mechanism, MushroomNet, which applies the lightweight network MobileNetV3 as the backbone model, combined with the attention structure proposed by us, and has achieved excellent performance in the mushroom recognition task.
no code implementations • 30 Sep 2021 • Yihua Yang
In our model, with the neighbourhoods of airway taken into account, the graph structure is incorporated and the segmentation of airways are improved compared with the traditional CNN methods.
no code implementations • 25 Sep 2019 • Liu Liu, Lei Deng, Shuangchen Li, Jingwei Zhang, Yihua Yang, Zhenyu Gu, Yufei Ding, Yuan Xie
Using Recurrent Neural Networks (RNNs) in sequence modeling tasks is promising in delivering high-quality results but challenging to meet stringent latency requirements because of the memory-bound execution pattern of RNNs.