iLog 2.0: A Novel Method for Food Nutritional Value Automatic Quantification in Smart Healthcare-Reference-Cited by-同舟云学术

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iLog 2.0: A Novel Method for Food Nutritional Value Automatic Quantification in Smart Healthcare

Published:2022-12 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Symposium on Smart Electronic Systems (iSES)
language:
Short-container-title:

Author:

Mitra Alakananda¹,Goel Sarang²,Mohanty Saraju P.³,Kougianos Elias⁴,Rachakonda Laavanya⁵

Affiliation:

1. University of North Texas,Dept. of Computer Science and Engineering,USA

2. University of North Texas,Texas Academy of Mathematics and Science,USA

3. University of North Texas,Computer Science and Engineering,USA

4. Dept. of Electrical Engineering,USA

5. Univ. of North Carolina at Wilmington,Dept. of Computer Science

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10026847/10026888/10026951.pdf?arnumber=10026951

Reference37 articles.

1. A Food Recognition System for Diabetic Patients Based on an Optimized Bag-of-Features Model

2. A Machine Learning Based Approach for Deepfake Detection in Social Media Through Key Video Frame Extraction

3. Towards Computer Vision Powered Color-Nutrient Assessment of Puréed Food

4. SSD: Single shot multibox detector;liu;Proc European Conference on Computer Vision,2016

5. A Study of Multi-Task and Region-Wise Deep Learning for Food Ingredient Recognition

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. FruitPAL: A Smart Healthcare Framework for Automatic Detection of Fruit Allergens;2023 IEEE International Symposium on Smart Electronic Systems (iSES);2023-12-18

2. FruitPAL 2.0: A Smart Healthcare Framework for Automatic Monitoring of Fruit Consumption;2023 OITS International Conference on Information Technology (OCIT);2023-12-13

3. FruitPAL: An IoT-Enabled Framework for Automatic Monitoring of Fruit Consumption in Smart Healthcare

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