Fractal Microstructure of Foods

García‐Armenta, Evangelina; Gutiérrez-López, Gustavo F.

doi:10.1007/s12393-021-09302-y

Food Eng Rev

2022

DOI: 10.1007/s12393-021-09302-y

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Fractal Microstructure of Foods

Evangelina García‐Armenta

Gustavo F. Gutiérrez-López

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2024

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Cited by 8 publications

References 144 publications

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Automatic Food Recognition Using Deep Convolutional Neural Networks with Self-attention Mechanism

Abiyev,

Adepoju

2024

Hum-Cent Intell Syst

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The significance of food in human health and well-being cannot be overemphasized. Nowadays, in our dynamic life, people are increasingly concerned about their health due to increased nutritional ailments. For this reason, mobile food-tracking applications that require a reliable and robust food classification system are gaining popularity. To address this, we propose a robust food recognition model using deep convolutional neural networks with a self-attention mechanism (FRCNNSAM). By training multiple FRCNNSAM structures with varying parameters, we combine their predictions through averaging. To prevent over-fitting and under-fitting data augmentation to generate extra training data, regularization to avoid excessive model complexity was used. The FRCNNSAM model is tested on two novel datasets: Food-101 and MA Food-121. The model achieved an impressive accuracy of 96.40% on the Food-101 dataset and 95.11% on MA Food-121. Compared to baseline transfer learning models, the FRCNNSAM model surpasses performance by 8.12%. Furthermore, the evaluation on random internet images demonstrates the model's strong generalization ability, rendering it suitable for food image recognition and classification tasks.

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Automatic Food Recognition Using Deep Convolutional Neural Networks with Self-attention Mechanism

Abiyev,

Adepoju

2024

Hum-Cent Intell Syst

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Effect of high-voltage electrostatic field treatments on bananas (Musa paradisiaca var. sapientum) on their postharvest quality, enzymatic activity and morphological changes

Valdez-Miranda,

Robles-López,

Robles-de-la-Torre

et al. 2024

Food and Bioproducts Processing

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A comprehensive study from the micro- to the nanometric scale: Evaluation of chilling injury in tomato fruit (Solanum lycopersicum)

Acosta-Ramírez,

Lares-Carrillo,

Ayón-Reyna

et al. 2024

Food Research International

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Fractal Microstructure of Foods

Cited by 8 publications

References 144 publications

Automatic Food Recognition Using Deep Convolutional Neural Networks with Self-attention Mechanism

Automatic Food Recognition Using Deep Convolutional Neural Networks with Self-attention Mechanism

Effect of high-voltage electrostatic field treatments on bananas (Musa paradisiaca var. sapientum) on their postharvest quality, enzymatic activity and morphological changes

A comprehensive study from the micro- to the nanometric scale: Evaluation of chilling injury in tomato fruit (Solanum lycopersicum)

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