Meta-Learning-Based Lightweight Method for Food Calorie Estimation
As a significant research component in nutritional assessment, vision-based food calorie estimation has been studied and applied due to its higher accuracy and efficiency. In this paper, a lightweight network for food calorie estimation is designed, called MeLL-cal. Firstly, a feature extraction mod...
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| Format: | Article |
| Language: | English |
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Wiley
2025-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/jfq/7044178 |
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| author | Jinlin Ma Yuetong Wan Ziping Ma |
| author_facet | Jinlin Ma Yuetong Wan Ziping Ma |
| author_sort | Jinlin Ma |
| collection | DOAJ |
| description | As a significant research component in nutritional assessment, vision-based food calorie estimation has been studied and applied due to its higher accuracy and efficiency. In this paper, a lightweight network for food calorie estimation is designed, called MeLL-cal. Firstly, a feature extraction module is proposed based on meta-learning ideas to generate informative representations, such as color, texture, and edge features, for unseen foods. Secondly, within the feature extraction module, a large convolutional kernel is proposed to provide a larger receptive field, which aims to capture more shape and semantic information and minimize information loss. Then, to achieve efficient calorie estimation with lower computational complexity, the calorie estimation module employs query-based inference to achieve optimal feature expression. Additionally, an adaptive fine-tuning module is also designed to refine estimation accuracy according to different datasets. The extensive experiments demonstrate the superiority of the MeLL-cal in terms of a PMAE of 18.7% and 31.1%, respectively, with only 2.313K parameters and 1.036 ms inference time on the Menu match dataset and the Calo world dataset. |
| format | Article |
| id | doaj-art-832430e1637640a2a3fea5f62e9636a8 |
| institution | DOAJ |
| issn | 1745-4557 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Food Quality |
| spelling | doaj-art-832430e1637640a2a3fea5f62e9636a82025-08-20T02:57:57ZengWileyJournal of Food Quality1745-45572025-01-01202510.1155/jfq/7044178Meta-Learning-Based Lightweight Method for Food Calorie EstimationJinlin Ma0Yuetong Wan1Ziping Ma2School of Computer Science and EngineeringSchool of Computer Science and EngineeringSchool of Mathematics and Information ScienceAs a significant research component in nutritional assessment, vision-based food calorie estimation has been studied and applied due to its higher accuracy and efficiency. In this paper, a lightweight network for food calorie estimation is designed, called MeLL-cal. Firstly, a feature extraction module is proposed based on meta-learning ideas to generate informative representations, such as color, texture, and edge features, for unseen foods. Secondly, within the feature extraction module, a large convolutional kernel is proposed to provide a larger receptive field, which aims to capture more shape and semantic information and minimize information loss. Then, to achieve efficient calorie estimation with lower computational complexity, the calorie estimation module employs query-based inference to achieve optimal feature expression. Additionally, an adaptive fine-tuning module is also designed to refine estimation accuracy according to different datasets. The extensive experiments demonstrate the superiority of the MeLL-cal in terms of a PMAE of 18.7% and 31.1%, respectively, with only 2.313K parameters and 1.036 ms inference time on the Menu match dataset and the Calo world dataset.http://dx.doi.org/10.1155/jfq/7044178 |
| spellingShingle | Jinlin Ma Yuetong Wan Ziping Ma Meta-Learning-Based Lightweight Method for Food Calorie Estimation Journal of Food Quality |
| title | Meta-Learning-Based Lightweight Method for Food Calorie Estimation |
| title_full | Meta-Learning-Based Lightweight Method for Food Calorie Estimation |
| title_fullStr | Meta-Learning-Based Lightweight Method for Food Calorie Estimation |
| title_full_unstemmed | Meta-Learning-Based Lightweight Method for Food Calorie Estimation |
| title_short | Meta-Learning-Based Lightweight Method for Food Calorie Estimation |
| title_sort | meta learning based lightweight method for food calorie estimation |
| url | http://dx.doi.org/10.1155/jfq/7044178 |
| work_keys_str_mv | AT jinlinma metalearningbasedlightweightmethodforfoodcalorieestimation AT yuetongwan metalearningbasedlightweightmethodforfoodcalorieestimation AT zipingma metalearningbasedlightweightmethodforfoodcalorieestimation |