Spiking neural networks (SNNs) are emerging as an energy-efficient alternative to traditional
artificial neural networks (ANNs) due to their unique spike-based event-driven nature …

Autonomous driving demands an integrated approach that encompasses perception,
prediction, and planning, all while operating under strict energy constraints to enhance …

The complexity of convolutional neural network architectures in hyperspectral image
classification tasks results in long training times and high energy consumption, which …