2 citations · 2 across the 5 of their papers we have counts for
5 papers
EncodeNet: A Framework for Boosting DNN Accuracy with Entropy-driven Generalized Converting Autoencoder
Hasanul Mahmud, Kevin Desai, Palden Lama +1
Image classification is a fundamental task in computer vision, and the quest to enhance DNN accuracy without inflating model size or latency remains a pressing concern. We make a c…
A Parallel Workflow for Polar Sea-Ice Classification using Auto-labeling of Sentinel-2 Imagery
Jurdana Masuma Iqrah, Wei Wang, Hongjie Xie +1
The observation of the advancing and retreating pattern of polar sea ice cover stands as a vital indicator of global warming. This research aims to develop a robust, effective, and…
A Converting Autoencoder Toward Low-latency and Energy-efficient DNN Inference at the Edge
Hasanul Mahmud, Peng Kang, Kevin Desai +2
Reducing inference time and energy usage while maintaining prediction accuracy has become a significant concern for deep neural networks (DNN) inference on resource-constrained edg…
Report on 2023 CyberTraining PI Meeting, 26-27 September 2023
Geoffrey Fox, Mary P Thomas, Sajal Bhatia +20
This document describes a two-day meeting held for the Principal Investigators (PIs) of NSF CyberTraining grants. The report covers invited talks, panels, and six breakout sessions…
Toward Polar Sea-Ice Classification using Color-based Segmentation and Auto-labeling of Sentinel-2 Imagery to Train an Efficient Deep Learning Model
Jurdana Masuma Iqrah, Younghyun Koo, Wei Wang +2
Global warming is an urgent issue that is generating catastrophic environmental changes, such as the melting of sea ice and glaciers, particularly in the polar regions. The melting…