Zobrazeno 1 - 10
of 130
pro vyhledávání: '"Jinyong Cheng"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-20 (2024)
Abstract During music recommendation scenarios, sparsity and cold start problems are inevitable. Auxiliary information has been utilized in music recommendation algorithms to provide users with more accurate music recommendation results. This study p
Externí odkaz:
https://doaj.org/article/d9fe3c9c0ec042d0a0e842c6c71eebb4
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 16, Iss 1, Pp 1-18 (2023)
Abstract Melanoma is a fatal skin disease, and there are many challenging tasks in the detection of melanoma through neural network at this stage. We propose a new method for melanoma diagnosis based on EfficientNet and patch strategy. The diagnosis
Externí odkaz:
https://doaj.org/article/d0a95e16027e4d8aa1894c023bcb8f39
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 21, Iss 1, Pp 1-12 (2021)
Abstract Background Currently, cardiovascular disease has become a major disease endangering human health, and the number of such patients is growing. Electrocardiogram (ECG) is an important basis for {medical doctors to diagnose the cardiovascular d
Externí odkaz:
https://doaj.org/article/a4fee6c19d484043a6d190514d63d1e6
Autor:
Ying Xu, Jinyong Cheng
Publikováno v:
Mathematical Biosciences and Engineering, Vol 18, Iss 4, Pp 3404-3422 (2021)
To fully extract the local and long-range information of amino acid sequences and enhance the effective information, this research proposes a secondary structure prediction model of protein based on a multi-scale convolutional attentional neural netw
Externí odkaz:
https://doaj.org/article/2fd534993cda441183bff056e8688bc9
Publikováno v:
Biotechnology & Biotechnological Equipment, Vol 35, Iss 1, Pp 1881-1890 (2021)
Proteins play a vital role in organisms, which suggests that in-depth study of the function of proteins is helpful to the application of proteins in a more accurate and effective way. Accordingly, protein structure will become the focus of discussion
Externí odkaz:
https://doaj.org/article/e4d03b3d428446498485941d8c4f8289
Autor:
Ying Xu, Jinyong Cheng
Publikováno v:
IEEE Access, Vol 8, Pp 183972-183982 (2020)
The representation-based classification method has become a research hotspot in recent years. Representation-based classifiers assign class labels directly to test samples based on a structured dictionary. The structured dictionary is composed of tra
Externí odkaz:
https://doaj.org/article/d1f4e3f88fbc415eb6d6ae9d1d287824
Autor:
Zhisheng Yang, Jinyong Cheng
Publikováno v:
PeerJ Computer Science, Vol 7, p e822 (2021)
In the field of deep learning, the processing of large network models on billions or even tens of billions of nodes and numerous edge types is still flawed, and the accuracy of recommendations is greatly compromised when large network embeddings are
Externí odkaz:
https://doaj.org/article/31531074340c444bb4dec5d2b2285d6b
Autor:
Zhisheng Yang, Jinyong Cheng
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 14, Iss 1 (2021)
In recommendation algorithms, data sparsity and cold start problems are inevitable. To solve such problems, researchers apply auxiliary information to recommendation algorithms, mine users’ historical records to obtain more potential information, a
Externí odkaz:
https://doaj.org/article/80e0b0ffbb944fd4bc205180509544de
Autor:
Lingzhi Kong, Jinyong Cheng
Publikováno v:
PLoS ONE, Vol 16, Iss 11 (2021)
Pneumonia remains the leading infectious cause of death in children under the age of five, killing about 700,000 children each year and affecting 7% of the world’s population. X-ray images of lung become the key to the diagnosis of this disease, sk
Externí odkaz:
https://doaj.org/article/2ae8d7d192e3463c95856f20c1dc9fcc
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a6760c86391e1d6d332f07aaabf0073a
https://doi.org/10.1109/icassp49357.2023.10094911
https://doi.org/10.1109/icassp49357.2023.10094911