Zobrazeno 1 - 10
of 133
pro vyhledávání: '"Abbasi, Saad"'
Vision transformers have shown unprecedented levels of performance in tackling various visual perception tasks in recent years. However, the architectural and computational complexity of such network architectures have made them challenging to deploy
Externí odkaz:
http://arxiv.org/abs/2308.11421
Autor:
Wong, Alexander, Wu, Yifan, Abbasi, Saad, Nair, Saeejith, Chen, Yuhao, Shafiee, Mohammad Javad
Multi-task learning has shown considerable promise for improving the performance of deep learning-driven vision systems for the purpose of robotic grasping. However, high architectural and computational complexity can result in poor suitability for d
Externí odkaz:
http://arxiv.org/abs/2304.11196
There can be numerous electronic components on a given PCB, making the task of visual inspection to detect defects very time-consuming and prone to error, especially at scale. There has thus been significant interest in automatic PCB component detect
Externí odkaz:
http://arxiv.org/abs/2301.09268
As the COVID-19 pandemic continues to put a significant burden on healthcare systems worldwide, there has been growing interest in finding inexpensive symptom pre-screening and recommendation methods to assist in efficiently using available medical r
Externí odkaz:
http://arxiv.org/abs/2211.11944
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. Recently, the introduction of attention condenser networks have resu
Externí odkaz:
http://arxiv.org/abs/2208.06980
Deep neural network (DNN) latency characterization is a time-consuming process and adds significant cost to Neural Architecture Search (NAS) processes when searching for efficient convolutional neural networks for embedded vision applications. DNN La
Externí odkaz:
http://arxiv.org/abs/2205.12660
Neural Architecture Search (NAS) has enabled automatic discovery of more efficient neural network architectures, especially for mobile and embedded vision applications. Although recent research has proposed ways of quickly estimating latency on unsee
Externí odkaz:
http://arxiv.org/abs/2204.12950
Modern deep neural networks must demonstrate state-of-the-art accuracy while exhibiting low latency and energy consumption. As such, neural architecture search (NAS) algorithms take these two constraints into account when generating a new architectur
Externí odkaz:
http://arxiv.org/abs/2111.15106
Autor:
Chung, Audrey G., Pavlova, Maya, Gunraj, Hayden, Terhljan, Naomi, MacLean, Alexander, Aboutalebi, Hossein, Surana, Siddharth, Zhao, Andy, Abbasi, Saad, Wong, Alexander
As the COVID-19 pandemic continues to devastate globally, one promising field of research is machine learning-driven computer vision to streamline various parts of the COVID-19 clinical workflow. These machine learning methods are typically stand-alo
Externí odkaz:
http://arxiv.org/abs/2109.06421
Autor:
MacLean, Alexander, Abbasi, Saad, Ebadi, Ashkan, Zhao, Andy, Pavlova, Maya, Gunraj, Hayden, Xi, Pengcheng, Kohli, Sonny, Wong, Alexander
The Coronavirus Disease 2019 (COVID-19) pandemic has impacted many aspects of life globally, and a critical factor in mitigating its effects is screening individuals for infections, thereby allowing for both proper treatment for those individuals as
Externí odkaz:
http://arxiv.org/abs/2108.03131