71 citations · 407 across the 58 of their papers we have counts for
6 papers · 1 filter
Dynamic Representations Toward Efficient Inference on Deep Neural Networks by Decision Gates
Mohammad Saeed Shafiee, Mohammad Javad Shafiee, Alexander Wong
While deep neural networks extract rich features from the input data, the current trade-off between depth and computational cost makes it difficult to adopt deep neural networks fo…
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…
Unsupervised Feature Learning Toward a Real-time Vehicle Make and Model Recognition
Amir Nazemi, Mohammad Javad Shafiee, Zohreh Azimifar +1
Vehicle Make and Model Recognition (MMR) systems provide a fully automatic framework to recognize and classify different vehicle models. Several approaches have been proposed to ad…
MicronNet: A Highly Compact Deep Convolutional Neural Network Architecture for Real-time Embedded Traffic Sign Classification
Alexander Wong, Mohammad Javad Shafiee, Michael St. Jules
Traffic sign recognition is a very important computer vision task for a number of real-world applications such as intelligent transportation surveillance and analysis. While deep n…
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…