Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Zuqiang Meng"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)
Abstract It is essential to delve into the strategy of multimodal model pre-training, which is an obvious impact on downstream tasks. Currently, clustering learning has achieved noteworthy benefits in multiple methods. However, due to the availabilit
Externí odkaz:
https://doaj.org/article/a8ac5e46876c44c587def0f7e7f467fa
Autor:
Yang Xu, Zuqiang Meng
Publikováno v:
IET Image Processing, Vol 18, Iss 7, Pp 1927-1937 (2024)
Abstract Over the past few years, the COVID‐19 virus has had a significant impact on the physical and mental health of people around the world. Therefore, in order to effectively distinguish COVID‐19 patients, many deep learning efforts have used
Externí odkaz:
https://doaj.org/article/e792405005ff43e1a0c39566c1d7ebf8
Publikováno v:
IET Computer Vision, Vol 17, Iss 4, Pp 473-482 (2023)
Abstract Learning subtle discriminative feature representation plays a significant role in Fine‐Grained Visual Categorisation (FGVC). The vision transformer (ViT) achieves promising performance in the traditional image classification filed due to i
Externí odkaz:
https://doaj.org/article/2edcb01f701b455785bd71bda3282e87
Publikováno v:
AI Open, Vol 4, Iss , Pp 130-136 (2023)
- Accurate discriminative region proposal has an important effect for fine-grained image recognition. The vision transformer (ViT) brings about a striking effect in computer vision due to its innate multi-head self-attention mechanism. However, the a
Externí odkaz:
https://doaj.org/article/515b0a6d6e8d470698e2ab42913f2e8a
Autor:
Yi Liang, Zuqiang Meng
Publikováno v:
IEEE Access, Vol 11, Pp 100508-100517 (2023)
Breast cancer is a prevalent disease worldwide, and early diagnosis plays a vital role in improving patient outcomes. Recent advancements in deep learning have shown great potential for accurate and efficient breast cancer classification. However, th
Externí odkaz:
https://doaj.org/article/694d759152e24f9782374dc7e63efce9
Publikováno v:
BMC Bioinformatics, Vol 23, Iss 1, Pp 1-21 (2022)
Abstract Background Amino acid property-aware phylogenetic analysis (APPA) refers to the phylogenetic analysis method based on amino acid property encoding, which is used for understanding and inferring evolutionary relationships between species from
Externí odkaz:
https://doaj.org/article/0e1a8eb55df94e7b871bcdb772783e29
Autor:
Lin Wang, Zuqiang Meng
Publikováno v:
Sensors, Vol 22, Iss 3, p 714 (2022)
In Chinese sentiment analysis tasks, many existing methods tend to use recurrent neural networks (e.g., long short-term memory networks and gated recurrent units) and standard one-dimensional convolutional neural networks (1D-CNN) to extract features
Externí odkaz:
https://doaj.org/article/c41e4e49e2c843db9ee2d8bea0a6e592
Autor:
Liwei Jing, Lina Yang, Yujian Yuan, Zuqiang Meng, Yifeng Tan, Patrick Shen-Pei Wang, Xichun Li
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e7a8377f208176bd43f3b8c39be7307a
https://doi.org/10.1142/s0218001423530026
https://doi.org/10.1142/s0218001423530026
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. 37
Relation classification as a core technique for building knowledge graphs becomes a critical task in natural language processing. The fact that humans can learn by summarizing and generalizing limited knowledge motivates scholars to explore few-shot
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::58c74d386701f9fc967a0883932db358
https://doi.org/10.1142/s0218001423500106
https://doi.org/10.1142/s0218001423500106
Autor:
Haoyan Yang, Lina Yang, Thomas Wu, Zuqiang Meng, Youju Huang, Patrick Shen-Pei Wang, Peng Li, Xichun Li
Publikováno v:
International Journal of Pattern Recognition and Artificial Intelligence. 36
Bridge crack detection is a key task in the structural health monitoring of Civil Engineering. In the traditional bridge crack detection methods, there exist some problems such as high cost, low speed, and complex structure. This paper developed a br
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f11fa9865035a6cdd49a6b0d00e91f0b
https://doi.org/10.1142/s0218001422500471
https://doi.org/10.1142/s0218001422500471