activity
20182021
most citedTowards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation

3 citations · 5 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2021

An Integrated System for Mobile Image-Based Dietary Assessment

Zeman Shao, Yue Han, Jiangpeng He +5

Accurate assessment of dietary intake requires improved tools to overcome limitations of current methods including user burden and measurement error. Emerging technologies such as…

eess.SP20211 cited

Motion Artifact Reduction In Photoplethysmography For Reliable Signal Selection

Runyu Mao, Mackenzie Tweardy, Stephan W. Wegerich +3

Photoplethysmography (PPG) is a non-invasive and economical technique to extract vital signs of the human body. Although it has been widely used in consumer and research grade wris…

cs.CV2021

Improving Dietary Assessment Via Integrated Hierarchy Food Classification

Runyu Mao, Jiangpeng He, Luotao Lin +3

Image-based dietary assessment refers to the process of determining what someone eats and how much energy and nutrients are consumed from visual data. Food classification is the fi…

cs.CV20213 cited

Towards Learning Food Portion From Monocular Images With Cross-Domain Feature Adaptation

Zeman Shao, Shaobo Fang, Runyu Mao +5

We aim to estimate food portion size, a property that is strongly related to the presence of food object in 3D space, from single monocular images under real life setting. Specific…

cs.CV20211 cited

An End-to-End Food Image Analysis System

Jiangpeng He, Runyu Mao, Zeman Shao +4

Modern deep learning techniques have enabled advances in image-based dietary assessment such as food recognition and food portion size estimation. Valuable information on the types…

cs.CV2020

Visual Aware Hierarchy Based Food Recognition

Runyu Mao, Jiangpeng He, Zeman Shao +2

Food recognition is one of the most important components in image-based dietary assessment. However, due to the different complexity level of food images and inter-class similarity…