71 citations · 103 across the 6 of their papers we have counts for
5 papers · 1 filter
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…
Human-Machine Collaborative Design for Accelerated Design of Compact Deep Neural Networks for Autonomous Driving
Mohammad Javad Shafiee, Mirko Nentwig, Yohannes Kassahun +7
An effective deep learning development process is critical for widespread industrial adoption, particularly in the automotive sector. A typical industrial deep learning development…
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…
Fast YOLO: A Fast You Only Look Once System for Real-time Embedded Object Detection in Video
Mohammad Javad Shafiee, Brendan Chywl, Francis Li +1
Object detection is considered one of the most challenging problems in this field of computer vision, as it involves the combination of object classification and object localizatio…