Results 31 to 40 of about 663,658 (295)

Time Series Forecasting and Classification Models Based on Recurrent with Attention Mechanism and Generative Adversarial Networks

Sensors, 2020
Time series classification and forecasting have long been studied with the traditional statistical methods. Recently, deep learning achieved remarkable successes in areas such as image, text, video, audio processing, etc.
Kun Zhou, Wenyong Wang, Teng Hu, Kai Deng   +3 more
doaj   +1 more source

Filamentary Switching: Synaptic Plasticity through Device Volatility

, 2015
Replicating the computational functionalities and performances of the brain remains one of the biggest challenges for the future of information and communication technologies.
Alibart, Fabien, La Barbera, Selina, Vuillaume, Dominique   +2 more
core   +3 more sources

Responses of adult crayfish to macro-nutrients intake alteration during juvenile stage on metabolism and intestinal microbiota

Aquaculture Reports
Red swamp crayfish Procambarus clarkii is becoming an ecologically and economically important crustacean species in China. In present study, whether the macro-nutrients intake intervention during early life in crayfish resulting long-term influences on ...
Yan Shui, Shengyan Su, Zenghong Xu, Zhiqiang Xu   +3 more
doaj   +1 more source

Long-term target tracking combined with re-detection

EURASIP Journal on Advances in Signal Processing, 2021
Long-term visual tracking undergoes more challenges and is closer to realistic applications than short-term tracking. However, the performances of most existing methods have been limited in the long-term tracking tasks.
Juanjuan Wang, Haoran Yang, Ning Xu, Chengqin Wu, Zengshun Zhao, Jixiang Zhang, Dapeng Oliver Wu   +6 more
doaj   +1 more source

Streamflow Prediction in the Mekong River Basin Using Deep Neural Networks

IEEE Access, 2023
In recent years, the Mekong River Basin (MRB), one of the largest river basins in Southeast Asia, has experienced severe impacts from extreme droughts and floods.
Thi-Thu-Ha Nguyen, Duc-Quang Vu, Son T. Mai, Thanh Duc Dang   +3 more
doaj   +1 more source

3D Randomized Connection Network with Graph-based Label Inference

, 2017
In this paper, a novel 3D deep learning network is proposed for brain MR image segmentation with randomized connection, which can decrease the dependency between layers and increase the network capacity.
Bao, Siqi, Chung, Albert C. S., Mok, Tony C. W., Wang, Pei   +3 more
core   +1 more source

Relational and conjunctive binding functions dissociate in short-term memory [PDF]

, 2015
Remembering complex events requires binding features within unified objects (conjunctions) and holding associations between objects (relations). Recent studies suggest that the two functions dissociate in long-term memory (LTM). Less is known about their
Cubelli, Roberto, Della Sala, Sergio, Fabi, Katia, Luzzi, Simona, Parra, Mario A, Valdes Hernandez, Maria   +5 more
core   +1 more source

Long-Term Microgravity Effects on Isometric Handgrip and Precision Pinch Force with Visual and Proprioceptive Feedback

International Journal of Aerospace Engineering, 2018
The study and analysis of human physiology during short- and long-duration space flights are the most valuable approach in order to evaluate the effect of microgravity on the human body and to develop possible countermeasures in prevision of future ...
Ilario Puglia, Michele Balsamo, Marco Vukich, Valfredo Zolesi   +3 more
doaj   +1 more source

Joint Timekeeping of Navigation Satellite Constellation with Inter-Satellite Links

Sensors, 2020
As a system of ranging and positioning based on time transfer, the timekeeping ability of a navigation satellite constellation is a key factor for accurate positioning and timing services. As the timekeeping performances depend on the frequency stability
Leyuan Sun, Wende Huang, Shuaihe Gao, Wei Li, Xiye Guo, Jun Yang   +5 more
doaj   +1 more source

Gated Recurrent Neural Tensor Network

, 2017
Recurrent Neural Networks (RNNs), which are a powerful scheme for modeling temporal and sequential data need to capture long-term dependencies on datasets and represent them in hidden layers with a powerful model to capture more information from inputs ...
Adriani, Mirna, Manurung, Ruli, Nakamura, Satoshi, Sakti, Sakriani, Tjandra, Andros   +4 more
core   +1 more source