Abstract
Active Foreground Neural Network (AFNN) is a revolutionary neural network which aims at bridging the computation, learning, and application’s implementation gap across conventional neural networks and cognitive learning processes with dual-band training and application layers. The aim is to perform asynchronous and parallel training of cross-interface Artificial Intelligence models with simultaneous implementation of the same. Therefore, the user may or may not need to implement the learning model.
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Aggarwal, A., Gupta, S.C. (2019). Active Foreground Neural Network. In: Mishra, S., Sood, Y., Tomar, A. (eds) Applications of Computing, Automation and Wireless Systems in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-13-6772-4_45
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DOI: https://doi.org/10.1007/978-981-13-6772-4_45
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