1 citations · 1 across the 2 of their papers we have counts for
4 papers
A Time- and Energy-Efficient CNN with Dense Connections on Memristor-Based Chips
Wenyong Zhou, Yuan Ren, Jiajun Zhou +2
Designing lightweight convolutional neural network (CNN) models is an active research area in edge AI. Compute-in-memory (CIM) provides a new computing paradigm to alleviate time a…
A Unifying Tensor View for Lightweight CNNs
Jason Chun Lok Li, Rui Lin, Jiajun Zhou +2
Despite the decomposition of convolutional kernels for lightweight CNNs being well studied, existing works that rely on tensor network diagrams or hyperdimensional abstraction lack…
Hundred-Kilobyte Lookup Tables for Efficient Single-Image Super-Resolution
Binxiao Huang, Jason Chun Lok Li, Jie Ran +4
Conventional super-resolution (SR) schemes make heavy use of convolutional neural networks (CNNs), which involve intensive multiply-accumulate (MAC) operations, and require special…
Lite it fly: An All-Deformable-Butterfly Network
Rui Lin, Jason Chun Lok Li, Jiajun Zhou +3
Most deep neural networks (DNNs) consist fundamentally of convolutional and/or fully connected layers, wherein the linear transform can be cast as the product between a filter matr…