6 citations · 6 across the 4 of their papers we have counts for
5 papers
ShatterQuant: Breaking Uniform Precision with Block-Wise Mixed-Precision on a Systolic Transformer Hardware Accelerator
Mikolaj Walczak, Edward Humes, Chao Fang +2
Due to limited support for intra-tensor heterogeneous precision in conventional accelerators, neural network quantization remains largely restricted to per-tensor precision assignm…
SatReg: Regression-based Neural Architecture Search for Lightweight Satellite Image Segmentation
Edward Humes, Tinoosh Mohsenin
As Earth-observation workloads move toward onboard and edge processing, remote-sensing segmentation models must operate under tight latency and energy constraints. We present SatRe…
Enabling On-Device Medical AI Assistants via Input-Driven Saliency Adaptation
Uttej Kallakurik, Edward Humes, Rithvik Jonna +2
Large Language Models (LLMs) have significant impact on the healthcare scenarios but remain prohibitively large for deployment in real-time, resource-constrained environments such…
RAFT -- A Domain Adaptation Framework for RGB & LiDAR Semantic Segmentation
Edward Humes, Xiaomin Lin, Boxun Hu +2
Image segmentation is a powerful computer vision technique for scene understanding. However, real-world deployment is stymied by the need for high-quality, meticulously labeled dat…
Squeezed Edge YOLO: Onboard Object Detection on Edge Devices
Edward Humes, Mozhgan Navardi, Tinoosh Mohsenin
Demand for efficient onboard object detection is increasing due to its key role in autonomous navigation. However, deploying object detection models such as YOLO on resource constr…