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20192026
most citedDepthNet Nano: A Highly Compact Self-Normalizing Neural Network for Monocular Depth Estimation

7 citations · 12 across the 7 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

Xray-Visual Models: Scaling Vision models on Industry Scale Data

Shlok Mishra, Tsung-Yu Lin, Linda Wang +24

We present Xray-Visual, a unified vision model architecture for large-scale image and video understanding trained on industry-scale social media data. Our model leverages over 15 b…

cs.CV2020

EmotionNet Nano: An Efficient Deep Convolutional Neural Network Design for Real-time Facial Expression Recognition

James Ren Hou Lee, Linda Wang, Alexander Wong

While recent advances in deep learning have led to significant improvements in facial expression classification (FEC), a major challenge that remains a bottleneck for the widesprea…

cs.CV2020★ 7 cited

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…

cs.CV2019★ 5 cited

Implications of Computer Vision Driven Assistive Technologies Towards Individuals with Visual Impairment

Linda Wang, Alexander Wong

Computer vision based technology is becoming ubiquitous in society. One application area that has seen an increase in computer vision is assistive technologies, specifically for th…

cs.CV2019

Enabling Computer Vision Driven Assistive Devices for the Visually Impaired via Micro-architecture Design Exploration

Linda Wang, Alexander Wong

Recent improvements in object detection have shown potential to aid in tasks where previous solutions were not able to achieve. A particular area is assistive devices for individua…