3 papers
cs.LG2024
ActNAS : Generating Efficient YOLO Models using Activation NAS
Sudhakar Sah, Ravish Kumar, Darshan C. Ganji +1
Activation functions introduce non-linearity into Neural Networks, enabling them to learn complex patterns. Different activation functions vary in speed and accuracy, ranging from…
cs.CV2024
Token Pruning using a Lightweight Background Aware Vision Transformer
Sudhakar Sah, Ravish Kumar, Honnesh Rohmetra +1
High runtime memory and high latency puts significant constraint on Vision Transformer training and inference, especially on edge devices. Token pruning reduces the number of input…
cs.CV2024
MCUBench: A Benchmark of Tiny Object Detectors on MCUs
Sudhakar Sah, Darshan C. Ganji, Matteo Grimaldi +4
We introduce MCUBench, a benchmark featuring over 100 YOLO-based object detection models evaluated on the VOC dataset across seven different MCUs. This benchmark provides detailed…