no code implementations • 9 Dec 2023 • Chaoquan Jiang, Jinqiang Wang, Rui Hu, Jitao Sang
To address this issue, We propose a language-assisted diagnostic method that uses texts instead of images to diagnose bugs in vision models based on multi-modal models (eg CLIP).
no code implementations • 20 Mar 2023 • Furong Duan, Tao Zhu, Jinqiang Wang, Liming Chen, Huansheng Ning, Yaping Wan
Sensor-based human activity segmentation and recognition are two important and challenging problems in many real-world applications and they have drawn increasing attention from the deep learning community in recent years.
no code implementations • 23 Mar 2022 • Jinqiang Wang, Tao Zhu, Liming Chen, Huansheng Ning, Yaping Wan
Compared with SimCLR, it redefines the negative pairs in the contrastive loss function by using unsupervised clustering methods to generate soft labels that mask other samples of the same cluster to avoid regarding them as negative samples.
no code implementations • 17 Nov 2021 • Jitao Sang, Jinqiang Wang, Rui Hu, Chaoquan Jiang
Deep network models perform excellently on In-Distribution (ID) data, but can significantly fail on Out-Of-Distribution (OOD) data.
no code implementations • 5 Sep 2021 • Jinqiang Wang, Tao Zhu, Jingyuan Gan, Liming Chen, Huansheng Ning, Yaping Wan
The experiment results show that the resampling augmentation method outperforms all state-of-the-art methods under a small amount of labeled data, on SimCLRHAR and MoCoHAR, with mean F1-score as the evaluation metric.