1 code implementation • 18 Oct 2022 • Yiming Li, Zhifang Guo, Zhirong Ye, Xiangdong Wang, Hong Liu, Yueliang Qian, Rui Tao, Long Yan, Kazushige Ouchi
For the frame-wise model, the ICT-TOSHIBA system of DCASE 2021 Task 4 is used.
1 code implementation • 5 Oct 2021 • Zhirong Ye, Xiangdong Wang, Hong Liu, Yueliang Qian, Rui Tao, Long Yan, Kazushige Ouchi
A critical issue with the frame-based model is that it pursues the best frame-level prediction rather than the best event-level prediction.
no code implementations • 6 Nov 2019 • Yong Ruan, Xiangdong Wang, Hong Liu, Zhigang Ou, Yun Gao, Jianfeng Cheng, Yueliang Qian
For this, we train transformer model using feature sequence of audio and their phoneme sequence with lexical stress marks.
1 code implementation • 11 Sep 2019 • Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian
In this paper, we describe in detail the system we submitted to DCASE2019 task 4: sound event detection (SED) in domestic environments.
1 code implementation • 6 Jun 2019 • Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian
Instead of designing a single model by considering a trade-off between the two sub-targets, we design a teacher model aiming at audio tagging to guide a student model aiming at boundary detection to learn using the unlabeled data.
1 code implementation • 24 May 2019 • Liwei Lin, Xiangdong Wang, Hong Liu, Yueliang Qian
In this paper, a special decision surface for the weakly-supervised sound event detection (SED) and a disentangled feature (DF) for the multi-label problem in polyphonic SED are proposed.
1 code implementation • 27 Nov 2018 • Renqiang Li, Hong Liu, Xiangdong Wan, Yueliang Qian
Braille dots detection is the core and basic step for Braille image recognition.
1 code implementation • The 13th Asian Conference on Computer Vision 2016 • Haomiao Ni, Hong Liu, Xiangdong Wang, Yueliang Qian
This paper proposes a novel human action recognition using the decision-level fusion of both skeleton and depth sequence.