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DeepMaker: A multi-objective optimization framework for deep neural networks in embedded systems. Microprocess. Microsyst. 2020, 73, 102989. [Google Scholar] [CrossRef] Loni, M.; Zoljodi, A.; Sinaei, S.; Daneshtalab, M.; Sjödin, M. Neuropower: Designing energy efficient convolutional ...
Recurrent Neural Networks are one of the most common Neural Networks used in Natural Language Processing because of its promising results. The applications of RNN in language models consist of two main approaches. We can either make the model predict or
Instead of a traditional game engine, the GameGAN model relies on neural networks to generate PAC-MAN’s environment. Also, the AI keeps track of the virtual world while remembering what’s already been generated to maintain visual consistency from frame to frame. The neural network model can ...
The simplified residual block diagram. Full size image Data acquisition In this paper, we used data sets of thermal videos that were captured from two BC systems Fig. 7. The thermal image datasets numbers one and two were captured from BC system number one. Through the first two experiments,...
The purpose of the DSS is to help the decision-maker facing the problem of huge amounts of data and ambiguous reactions of complicated systems depending on external factors. By means of accurate and profound analysis, DSSs are expected to provide the user with precisely forecasted indicators and...
S.K. Karmaker, M.M. Hassan, M.J. Smith, L. Xu, C. Zhai, K. Veeramachaneni AutoML to date and beyond: Challenges and opportunities ACM Computing Surveys (CSUR), 54 (8) (2021), pp. 1-36 CrossrefGoogle Scholar [19] M. Wever, A. Tornede, F. Mohr, E. Hüllermeier AutoML ...
Quantum decision-maker theory and simulation A quantum device simulating the human decision making process is introduced. It consists of quantum recurrent nets generating stochastic processes which re... M Zak,RE Meyers,KS Deacon - 《Proceedings of Spie the International Society for Optical Engineering...
In this paper, to precisely track the planar postures of multiple swimming multi-joint fish-like robots in real time, we propose a novel deep neural network-based method, named TAB-IOL. Its TAB part fuses the top-down and bottom-up approaches for vision-based pose estimation, while the ...
To demonstrate the usefulness of transfer learning, we also perform the direct training of the 5 models with the same ensemble network architecture and hyperparameters (the number of layers, the depth of layers, the kernel size, the dilation factor, and the learning rate) on the structured RNA...