no code implementations • 21 May 2023 • Huadai Liu, Rongjie Huang, Jinzheng He, Gang Sun, Ran Shen, Xize Cheng, Zhou Zhao
Speech-to-SQL (S2SQL) aims to convert spoken questions into SQL queries given relational databases, which has been traditionally implemented in a cascaded manner while facing the following challenges: 1) model training is faced with the major issue of data scarcity, where limited parallel data is available; and 2) the systems should be robust enough to handle diverse out-of-domain speech samples that differ from the source data.
no code implementations • 10 May 2023 • Ran Shen, Gang Sun, Hao Shen, Yiling Li, Liangfeng Jin, Han Jiang
Then, we construct data formats of different subtasks based on existing data and improve the accuracy of the overall model by improving the accuracy of each submodel.
1 code implementation • 21 Sep 2022 • Xiangzuo Huo, Gang Sun, Shengwei Tian, Yan Wang, Long Yu, Jun Long, Wendong Zhang, Aolun Li
A parallel hierarchy of local and global feature blocks is designed to efficiently extract local features and global representations at various semantic scales, with the flexibility to model at different scales and linear computational complexity relevant to image size.
no code implementations • 18 Feb 2022 • Xingjian Cao, Gang Sun, Hongfang Yu, Mohsen Guizani
Due to the differences of clients, a single global model may not perform well on all clients, so the personalized federated learning method, which trains a personalized model for each client that better suits its individual needs, becomes a research hotspot.
1 code implementation • 17 Feb 2022 • Xingjian Cao, Zonghang Li, Gang Sun, Hongfang Yu, Mohsen Guizani
CoFED is a federated learning method that is compatible with heterogeneous models, tasks, and training processes.
9 code implementations • NeurIPS 2018 • Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Andrea Vedaldi
We also propose a parametric gather-excite operator pair which yields further performance gains, relate it to the recently-introduced Squeeze-and-Excitation Networks, and analyse the effects of these changes to the CNN feature activation statistics.
82 code implementations • CVPR 2018 • Jie Hu, Li Shen, Samuel Albanie, Gang Sun, Enhua Wu
Squeeze-and-Excitation Networks formed the foundation of our ILSVRC 2017 classification submission which won first place and reduced the top-5 error to 2. 251%, surpassing the winning entry of 2016 by a relative improvement of ~25%.
Ranked #59 on Image Classification on CIFAR-10
no code implementations • CVPR 2016 • Wangjiang Zhu, Jie Hu, Gang Sun, Xudong Cao, Yu Qiao
Training with a large proportion of irrelevant volumes will hurt performance.
no code implementations • 13 Jan 2015 • Ren Wu, Shengen Yan, Yi Shan, Qingqing Dang, Gang Sun
We present a state-of-the-art image recognition system, Deep Image, developed using end-to-end deep learning.
no code implementations • CVPR 2013 • Li Shen, Shuhui Wang, Gang Sun, Shuqiang Jiang, Qingming Huang
For each internode of the hierarchical category structure, a discriminative dictionary and a set of classification models are learnt for visual categorization, and the dictionaries in different layers are learnt to exploit the discriminative visual properties of different granularity.