Automatic Recognition of Food Ingestion Environment from the AIM-2 Wearable Sensor

no code implementations • 13 May 2024 • Yuning Huang, Mohamed Abul Hassan, Jiangpeng He, Janine Higgins, Megan McCrory, Heather Eicher-Miller, Graham Thomas, Edward O Sazonov, Fengqing Maggie Zhu

Experimental results on the collected dataset show that our proposed method for automatic ingestion environment recognition successfully addresses the challenging data imbalance problem in the dataset and achieves a promising overall classification accuracy of 96. 63%.

imbalanced classification Transfer Learning

Long-tailed Food Classification

no code implementations • 26 Oct 2022 • Jiangpeng He, Luotao Lin, Heather Eicher-Miller, Fengqing Zhu

Food classification serves as the basic step of image-based dietary assessment to predict the types of foods in each input image.

Classification Data Augmentation +1

Towards the Creation of a Nutrition and Food Group Based Image Database

no code implementations • 5 Jun 2022 • Zeman Shao, Jiangpeng He, Ya-Yuan Yu, Luotao Lin, Alexandra Cowan, Heather Eicher-Miller, Fengqing Zhu

Food classification is critical to the analysis of nutrients comprising foods reported in dietary assessment.

Classification Nutrition