Zobrazeno 1 - 10
of 116
pro vyhledávání: '"Youfang Lin"'
Publikováno v:
Complex & Intelligent Systems, Vol 10, Iss 4, Pp 5261-5280 (2024)
Abstract Previous deep multi-agent reinforcement learning (MARL) algorithms have achieved impressive results, typically in symmetric and homogeneous scenarios. However, asymmetric heterogeneous scenarios are prevalent and usually harder to solve. In
Externí odkaz:
https://doaj.org/article/a74f8afa6d13485eb08f79e56b0adb5b
Publikováno v:
IEEE Transactions on Neural Systems and Rehabilitation Engineering, Vol 31, Pp 4470-4480 (2023)
The electroencephalogram (EEG) is extensively employed for detecting various brain electrical activities. Nonetheless, EEG recordings are susceptible to undesirable artifacts, resulting in misleading data analysis and even significantly impacting the
Externí odkaz:
https://doaj.org/article/40bd83de348141c7b8a3cd5b1e155e6d
Publikováno v:
Sensors, Vol 23, Iss 11, p 5152 (2023)
In vehicle re-identification, identifying a specific vehicle from a large image dataset is challenging due to occlusion and complex backgrounds. Deep models struggle to identify vehicles accurately when critical details are occluded or the background
Externí odkaz:
https://doaj.org/article/e6d1d0bbaa224738a56ad315364956cf
Publikováno v:
IEEE Access, Vol 8, Pp 133212-133224 (2020)
Ubiquitous Internet of Things (IoT) devices have fueled plenty of innovations in the emerging network paradigms. Among them, IoT edge caching has emerged as a promising technique to cope with the explosive growth in network data traffic, with Quality
Externí odkaz:
https://doaj.org/article/a724c57e0a9a47f782a42b16ddb2055b
Publikováno v:
PeerJ Computer Science, Vol 8, p e867 (2022)
Sequential recommendation has become a research trending that exploits user’s recent behaviors for recommendation. The user-item interactions contain a sequential dependency that we need to capture to better recommend. Item-item Product (IIP), whic
Externí odkaz:
https://doaj.org/article/ba61a19834074a3ea754c6d7ea69d4f5
Publikováno v:
PLoS ONE, Vol 17, Iss 6, p e0269651 (2022)
Item co-occurrence is an important pattern in recommendation. Due to the difference in correlation, the matching degrees between the target and historical items vary. The higher the matching degree, the greater probability they co-occur. Recently, th
Externí odkaz:
https://doaj.org/article/a9aeb82392c54e87b79806cf7559e630
Publikováno v:
Entropy, Vol 23, Iss 2, p 201 (2021)
We address the problem of unsupervised anomaly detection for multivariate data. Traditional machine learning based anomaly detection algorithms rely on specific assumptions of normal patterns and fail to model complex feature interactions and relatio
Externí odkaz:
https://doaj.org/article/cd6fba2d03c04916ad93ea8eecb6948d
Publikováno v:
PLoS ONE, Vol 9, Iss 1, p e86044 (2014)
ChIP-seq, which combines chromatin immunoprecipitation (ChIP) with next-generation parallel sequencing, allows for the genome-wide identification of protein-DNA interactions. This technology poses new challenges for the development of novel motif-fin
Externí odkaz:
https://doaj.org/article/d118fcccccfa4765a9b9629de0d7da9c
Autor:
Haomin Wen, Youfang Lin, Fan Wu, Huaiyu Wan, Zhongxiang Sun, Tianyue Cai, Hongyu Liu, Shengnan Guo, Jianbin Zheng, Chao Song, Lixia Wu
Publikováno v:
ACM Transactions on Intelligent Systems and Technology. 14:1-22
In intelligent logistics systems, predicting the Estimated Time of Pick-up Arrival (ETPA) of packages is a crucial task, which aims to predict the courier’s arrival time to all the unpicked-up packages at any time. Accurate prediction of ETPA can h
Publikováno v:
IEEE Transactions on Vehicular Technology. 72:4308-4319