56 citations · 129 across the 7 of their papers we have counts for
7 papers
YOLO Nano: a Highly Compact You Only Look Once Convolutional Neural Network for Object Detection
Alexander Wong, Mahmoud Famuori, Mohammad Javad Shafiee +3
Object detection remains an active area of research in the field of computer vision, and considerable advances and successes has been achieved in this area through the design of de…
EdgeSegNet: A Compact Network for Semantic Segmentation
Zhong Qiu Lin, Brendan Chwyl, Alexander Wong
In this study, we introduce EdgeSegNet, a compact deep convolutional neural network for the task of semantic segmentation. A human-machine collaborative design strategy is leverage…
AttoNets: Compact and Efficient Deep Neural Networks for the Edge via Human-Machine Collaborative Design
Alexander Wong, Zhong Qiu Lin, Brendan Chwyl
While deep neural networks have achieved state-of-the-art performance across a large number of complex tasks, it remains a big challenge to deploy such networks for practical, on-d…
FermiNets: Learning generative machines to generate efficient neural networks via generative synthesis
Alexander Wong, Mohammad Javad Shafiee, Brendan Chwyl +1
The tremendous potential exhibited by deep learning is often offset by architectural and computational complexity, making widespread deployment a challenge for edge scenarios such…
Tiny SSD: A Tiny Single-shot Detection Deep Convolutional Neural Network for Real-time Embedded Object Detection
Alexander Wong, Mohammad Javad Shafiee, Francis Li +1
Object detection is a major challenge in computer vision, involving both object classification and object localization within a scene. While deep neural networks have been shown in…
StressedNets: Efficient Feature Representations via Stress-induced Evolutionary Synthesis of Deep Neural Networks
Mohammad Javad Shafiee, Brendan Chwyl, Francis Li +4
The computational complexity of leveraging deep neural networks for extracting deep feature representations is a significant barrier to its widespread adoption, particularly for us…
SquishedNets: Squishing SqueezeNet further for edge device scenarios via deep evolutionary synthesis
Mohammad Javad Shafiee, Francis Li, Brendan Chwyl +1
While deep neural networks have been shown in recent years to outperform other machine learning methods in a wide range of applications, one of the biggest challenges with enabling…