Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Mingle Liu"'
Publikováno v:
IEEE Access, Vol 6, Pp 58043-58055 (2018)
Surveillance systems based on image analysis can automatically detect road accidents to ensure a quick intervention by rescue teams. However, in some situations, the visual information is insufficiently reliable, whereas the use of a sound detector c
Externí odkaz:
https://doaj.org/article/eebc7f2e129f496bb2746ea6ce4b5f4b
Recent efforts have been made on acoustic scene classification in the audio signal processing community. In contrast, few studies have been conducted on acoustic scene clustering, which is a newly emerging problem. Acoustic scene clustering aims at m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d4c1d23b22a4ddac81492b98477e5dc
http://arxiv.org/abs/2306.05621
http://arxiv.org/abs/2306.05621
Autor:
Qingguo Shao, Rabah Boukherroub, Mingle Liu, Yinghui Cai, Ning Cao, Xiaobei Zang, Teng Wang, Liu Peng, Fashun Li, Yijiang Qin
Publikováno v:
Journal of Materiomics
Journal of Materiomics, 2022, 8 (1), pp.113-122. ⟨10.1016/j.jmat.2021.04.012⟩
Journal of Materiomics, 2022, 8 (1), pp.113-122. ⟨10.1016/j.jmat.2021.04.012⟩
International audience; In this paper, porous partially fluorinated graphene (PFG) for supercapacitors (SCs) was fabricated by a mild and secure one-pot hydrothermal method utilizing weakly coordinating anion BF4− as the fluorine source. The hydrol
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8838156f45e0ce5081920884ef66b008
https://hal.science/hal-03561669
https://hal.science/hal-03561669
Autor:
Mingle Liu, Yupeng Qu, Xin Cheng, Tafadzwa Ronald Muzenda, Pengkun Hou, Jianrong Wang, Jie Shi
Publikováno v:
Journal of Thermal Analysis and Calorimetry. 141:1317-1330
The slow property gains of cement-based materials blended with industrial by-products such as fly ash (FA) and ground granulated blast-furnace slag (GGBS), especially at a high dosage, have been ascribed to be the main obstacle of increasing the sust
Publikováno v:
Multimedia Tools and Applications. 78:33999-34025
In this study, we propose a method for acoustic event diarization based on a feature of deep embedding and a clustering algorithm of integer linear programming. The deep embedding learned by deep auto-encoder network is used to represent the properti
Publikováno v:
IEEE Access, Vol 6, Pp 58043-58055 (2018)
Surveillance systems based on image analysis can automatically detect road accidents to ensure a quick intervention by rescue teams. However, in some situations, the visual information is insufficiently reliable, whereas the use of a sound detector c
Publikováno v:
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP
ICASSP
Convolutional recurrent neural networks (CRNNs) have achieved state-of-the-art performance for sound event detection (SED). In this paper, we propose to use a dilated CRNN, namely a CRNN with a dilated convolutional kernel, as the classifier for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2d0a4fb562bbf6306c0067118a841a16
http://arxiv.org/abs/1911.10888
http://arxiv.org/abs/1911.10888
Publikováno v:
Construction and Building Materials. 126:624-631
The synergistic effect of nano-silica (NS) and blast furnace slag (BFS) have been studied. A constant water-to-binder ratio (w/b) of 0.5 was used for all mortars. The different dosage (10%, 20%, 30% and 40%wt) of BFS and 3%wt NS were added into cemen
Publikováno v:
Construction and Building Materials. 262:120737
The combined utilization of mineral admixtures and nano-materials in cement-based composites is an inevitable trend based on the purpose of improving the durability. However, synergistic effect of mineral admixtures with nano-materials and their form
Publikováno v:
2018 International Conference on Audio, Language and Image Processing (ICALIP).
Although acoustic scene classification has been received great attention from researchers in the field of audio signal processing, it is still a challenging and unsolved task to date. In this paper, we present our work of acoustic scene classificatio