Static and dynamic precision adaptation for hardware learning and classification

Neural Computing

Static and dynamic precision adaptation for hardware learning and classification

Flexible and Efficient XNOR Circuit Architecture for Neural Network Based Deep Learning

Binary Neural Network for Improved Accuracy and Defense Against Bit-Flip Attacks

Connection Topology Optimization of Photovoltaic Arrays Using Neural Networks

Fault Classification in Photovoltaic Arrays Using Dropout and Pruned Neural Networks

Hardware-Noise-Aware Training for Improved Accuracy of In-Memory-Computing-Based Deep Neural Networks

Optimizing Solar Power using Array Topology Reconfiguration and Deep Neural Network

Multi-fidelity Data Aggregation using Convolutional Neural Networks

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