This paper introduces a lightweight uncertainty estimator capable of
pre...
In the expanding landscape of AI-enabled robotics, robust quantification...
The edge processing of deep neural networks (DNNs) is becoming increasin...
The rapid advancement of deep neural networks has significantly improved...
This work discusses memory-immersed collaborative digitization among
com...
Data-driven visual odometry (VO) is a critical subroutine for autonomous...
We propose MC-CIM, a compute-in-memory (CIM) framework for robust, yet l...
This work proposes a novel Energy-Aware Network Operator Search (ENOS)
a...
We propose a novel compute-in-memory (CIM)-based ultra-low-power framewo...
We propose a co-design approach for compute-in-memory inference for deep...
We present a novel low latency CMOS hardware accelerator for fully conne...
In this work, we introduce bitcell array-based support parameters to imp...