… enriched constantly with technical progress and deep application. … and isolation of the
DAMADICS benchmark problem[J]. … pulse coupled neural network and probability neural network[…

… ), which uses neural network modeling in traditional RL algo… these algorithms based on the
standard benchmark task “half-… The inner exploration mechanism where the reward function …

… An integrated information exchange pattern for measurement… , learning content and
persistence mechanism are analyzed. … capability of the benchmark model by simulating the inte…

… neural networks for NLP and their extended mechanism. The … can be extracted as a holistic
representation to characterize the … These two corpora have been widely used as benchmarks …

… operates based on a reward mechanism, where the agent … artificial neural networks,
computational models consisting of … -of-the-art results in numerous benchmarks. However, it …

… of the empirical models, the weakness of neural network is that … with Exogenous Inputs)
modelling concept was integrated into … method on a benchmark biological wastewater treatment …

… the marvelous advances in the development of deep neural … perception module and
integrated it with commonsense … based network with attention mechanism which is similar to [7…

… progress in numerous computer vision applications, particularly in human activity analysis. …
In each learning mechanism, we introduce efficient approaches to address action recognition …

… model ISR, which integrated modules of Pearson correlation coefficient, GloVe word embeddings,
and IDF weighting. The ISR model … due to the model’s retrieval matching mechanism. […

… attention mechanism, how do users interact with the model and … visualize CNN(Convolutional
neural networks) for classifying … benchmark. Then in order to find out the instance of the …