Given the challenges in reducing greenhouse gases (GHG), one of the sectors that have
attracted the most attention in the Sustainable Development Agenda 2030 (SDA-2030) is the …

Recently, handwritten Chinese character recognition has become an important research
field in computer vision. With the development of deep learning, convolutional neural …

Stochastic computing (SC) has become a promising approximate computing solution by its
negligible resource occupancy and ultralow energy consumption. As a potential …

Stochastic computing (SC) is an unconventional computing paradigm, which processes
numerical values through stochastic bitstreams. This representation can be interpreted as …

Deploying modern neural networks on resource-constrained edge devices necessitates a
series of optimizations to ready them for production. These optimizations typically involve …

There is a high energy cost associated with training Deep Neural Networks (DNNs). Off-chip
memory access contributes a major portion to the overall energy consumption. Reduction in …

Stochastic computing (SC) encodes numerical values into probabilistic binary bitstreams to
enable complex arithmetic operations to be transformed into simple bit operations. Different …

Stochastic computing (SC) is an unconventional computing paradigm with unique features.
Designing SC circuits is dramatically different from designing binary computing (BC) circuits …

Stochastic computing is a non‐traditional computing approach that utilizes stochastic
bitstreams to represent numerical values. This representation enables the implementation of …

Deep convolutional neural networks (DNNs) have achieved outstanding performance in this
field. Meanwhile, handwritten Chinese character recognition (HCCR) is a challenging area …