Artificial Intelligence (AI) has achieved significant advancements in technology and research
with the development over several decades, and is widely used in many areas including …

Convolutional neural networks (CNNs) can be quantized to reduce the bit-width of their
weights and activations. Pruning is another compression technique where entire structures …

Quantized neural networks employ reduced precision representations for both weights and
activations. This quantization process significantly reduces the memory requirements and …

Recently deep neural networks have achieved excellent performance on low-light raw video
enhancement. However they often come with high computational complexity and large …

There exists an innegligible performance gap between the binary neural networks and their
full-precision counterparts, which prevents their deployment on real-world applications …

Binary neural networks (BNNs), which have binary weights and activations, hold significant
potential for enabling neural computations on low-end edge devices with limited …