29 citations · 59 across the 14 of their papers we have counts for
8 papers · 1 filter
High-Throughput, High-Performance Deep Learning-Driven Light Guide Plate Surface Visual Quality Inspection Tailored for Real-World Manufacturing Environments
Carol Xu, Mahmoud Famouri, Gautam Bathla +2
Light guide plates are essential optical components widely used in a diverse range of applications ranging from medical lighting fixtures to back-lit TV displays. In this work, we…
Faster Attention Is What You Need: A Fast Self-Attention Neural Network Backbone Architecture for the Edge via Double-Condensing Attention Condensers
Alexander Wong, Mohammad Javad Shafiee, Saad Abbasi +2
With the growing adoption of deep learning for on-device TinyML applications, there has been an ever-increasing demand for efficient neural network backbones optimized for the edge…
TinyDefectNet: Highly Compact Deep Neural Network Architecture for High-Throughput Manufacturing Visual Quality Inspection
Mohammad Javad Shafiee, Mahmoud Famouri, Gautam Bathla +2
A critical aspect in the manufacturing process is the visual quality inspection of manufactured components for defects and flaws. Human-only visual inspection can be very time-cons…
AttendSeg: A Tiny Attention Condenser Neural Network for Semantic Segmentation on the Edge
Xiaoyu Wen, Mahmoud Famouri, Andrew Hryniowski +1
In this study, we introduce \textbf{AttendSeg}, a low-precision, highly compact deep neural network tailored for on-device semantic segmentation. AttendSeg possesses a self-attenti…
CancerNet-SCa: Tailored Deep Neural Network Designs for Detection of Skin Cancer from Dermoscopy Images
James Ren Hou Lee, Maya Pavlova, Mahmoud Famouri +1
Skin cancer continues to be the most frequently diagnosed form of cancer in the U.S., with not only significant effects on health and well-being but also significant economic costs…
AttendNets: Tiny Deep Image Recognition Neural Networks for the Edge via Visual Attention Condensers
Alexander Wong, Mahmoud Famouri, Mohammad Javad Shafiee
While significant advances in deep learning has resulted in state-of-the-art performance across a large number of complex visual perception tasks, the widespread deployment of deep…
DepthNet Nano: A Highly Compact Self-Normalizing Neural Network for Monocular Depth Estimation
Linda Wang, Mahmoud Famouri, Alexander Wong
Depth estimation is an active area of research in the field of computer vision, and has garnered significant interest due to its rising demand in a large number of applications ran…
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…