activity
20222025
most citedFaster Attention Is What You Need: A Fast Self-Attention Neural Network Backbone Architecture for the Edge via Double-Condensing Attention Condensers

5 citations · 13 across the 15 of their papers we have counts for

collaborators
Showing 2023Show all

9 papers · 1 filter

cs.CV2023★ 1 cited

NutritionVerse-Synth: An Open Access Synthetically Generated 2D Food Scene Dataset for Dietary Intake Estimation

Saeejith Nair, Chi-en Amy Tai, Yuhao Chen +1

Manually tracking nutritional intake via food diaries is error-prone and burdensome. Automated computer vision techniques show promise for dietary monitoring but require large and…

cs.AI2023

DARLEI: Deep Accelerated Reinforcement Learning with Evolutionary Intelligence

Saeejith Nair, Mohammad Javad Shafiee, Alexander Wong

We present DARLEI, a framework that combines evolutionary algorithms with parallelized reinforcement learning for efficiently training and evolving populations of UNIMAL agents. Ou…

cs.CV2023★ 1 cited

NAS-NeRF: Generative Neural Architecture Search for Neural Radiance Fields

Saeejith Nair, Yuhao Chen, Mohammad Javad Shafiee +1

Neural radiance fields (NeRFs) enable high-quality novel view synthesis, but their high computational complexity limits deployability. While existing neural-based solutions strive…

cs.CV2023

NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches

Chi-en Amy Tai, Matthew Keller, Saeejith Nair +8

Accurate dietary intake estimation is critical for informing policies and programs to support healthy eating, as malnutrition has been directly linked to decreased quality of life.…

cs.CV2023

TurboViT: Generating Fast Vision Transformers via Generative Architecture Search

Alexander Wong, Saad Abbasi, Saeejith Nair

Vision transformers have shown unprecedented levels of performance in tackling various visual perception tasks in recent years. However, the architectural and computational complex…

cs.CV2023★ 1 cited

Fast GraspNeXt: A Fast Self-Attention Neural Network Architecture for Multi-task Learning in Computer Vision Tasks for Robotic Grasping on the Edge

Alexander Wong, Yifan Wu, Saad Abbasi +3

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 architect…

cs.CV2023

NutritionVerse-Thin: An Optimized Strategy for Enabling Improved Rendering of 3D Thin Food Models

Chi-en Amy Tai, Jason Li, Sriram Kumar +4

With the growth in capabilities of generative models, there has been growing interest in using photo-realistic renders of common 3D food items to improve downstream tasks such as f…

cs.CV2023★ 1 cited

NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation

Chi-en Amy Tai, Matthew Keller, Mattie Kerrigan +4

77% of adults over 50 want to age in place today, presenting a major challenge to ensuring adequate nutritional intake. It has been reported that one in four older adults that are…

cs.CV2023★ 1 cited

PCBDet: An Efficient Deep Neural Network Object Detection Architecture for Automatic PCB Component Detection on the Edge

Brian Li, Steven Palayew, Francis Li +3

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. Ther…