To improve Asian food image classification accuracy, a method that combined Convolutional Block Attention Module (CBAM) with the Mobile NetV2, VGG16, and ResNet50 was proposed for Asian food image classification. Addi...To improve Asian food image classification accuracy, a method that combined Convolutional Block Attention Module (CBAM) with the Mobile NetV2, VGG16, and ResNet50 was proposed for Asian food image classification. Additionally, we proposed to use a mixed data enhancement algorithm (Mixup) to have a smoother discrimination ability. The effects of introducing the attention mechanism (CBAM) and using the mixed data enhancement algorithm (Mixup) were shown respectively through experimental comparison. The combination of these two and the final test set Top-1 accuracy rate reached 87.33%. Moreover, the information emphasized by CBAM was reflected through the visualization of the heat map. The results confirmed the classification method’s effectiveness and provided new ideas that improved Asian food image classification accuracy.展开更多
Food production in the countries of South and South-East Asia has shown a general upward trend during the last decade. Despite the considerable increase in population in many of these countries, food production per ca...Food production in the countries of South and South-East Asia has shown a general upward trend during the last decade. Despite the considerable increase in population in many of these countries, food production per capita in 1988-90 was significantly higher as compared to 1979-81 figures, the increase being specially marked in such countries as Vietnam, Cambodia, Indonesia, and Malaysia. Available daily calorie supply was adequate to meet the requirement. The overall pattern of food production however has shown little change, with cereal production continuing to account for a predominant part of food production. There is no evidence of a significant uptrend with respect to production of pulses, milk, horticultural products, poultry or meat production in most countries.A uniquc and unfortunate feature of the nutrition situation in South-Asian countries is that the incidence of low birth weight deliveries is as high as 34% (1990), ranging from 25% in Sri Lanka to 50% in Bangladesh (as against less than 7% in the countries of Europe and North America). Even in countries of Africa where the overall food and nutrition situation is worse than in South Asia, the incidence is well below 20%. This is a reflection of the poor state of maternal nutrition in pregnancy.Florid nutritional deficiency diseases have shown a steep decline over the last two decades, but goitre and iron deficiency anaemia continue to be major public health problems, though some headway has been made with regard to the control of the former. Severe forms of growth retardation in children have declined but the majority suffer from mild and moderate forms of growth retardation.Countries of the Region are in varying stages of developmental transition. Among the burgeoning middle classes in some of these countries there are evidences of escalation of degenerative diseases such as diabetes and coronary heart disease. With increasing life expectancy, geriatric nutritlonal problems will demand increasing attention展开更多
The detection and recognition of food pictures has become an emerging application field of computer vision. However, due to the small differences between the categories of food pictures and the large differences withi...The detection and recognition of food pictures has become an emerging application field of computer vision. However, due to the small differences between the categories of food pictures and the large differences within the categories, there are problems such as missed inspections and false inspections in the detection and recognition process. Aiming at the existing problems, an <span>improved YOLOv3 model of Asian food detection method is proposed.</span> Firstly, increase the top-down fusion path to form a circular fusion, making full use of shallow and deep features. Secondly, introduce the convolution residual <span>module to replace the ordinary convolution layer to increase the gradient</span> cor<span>relation and non-linearity of the network. Thirdly, introduce the CBAM</span> (Con<span>volutional Block Attention Module) attention mechanism to improve the</span> network’s ability to extract effective features. Finally, CIOU (Complete-IoU) loss is used to improve the convergence efficiency of the model. Experimental results show that the proposed improved model achieves better detection results on the Asian food UECFOOD100 data set.展开更多
文摘To improve Asian food image classification accuracy, a method that combined Convolutional Block Attention Module (CBAM) with the Mobile NetV2, VGG16, and ResNet50 was proposed for Asian food image classification. Additionally, we proposed to use a mixed data enhancement algorithm (Mixup) to have a smoother discrimination ability. The effects of introducing the attention mechanism (CBAM) and using the mixed data enhancement algorithm (Mixup) were shown respectively through experimental comparison. The combination of these two and the final test set Top-1 accuracy rate reached 87.33%. Moreover, the information emphasized by CBAM was reflected through the visualization of the heat map. The results confirmed the classification method’s effectiveness and provided new ideas that improved Asian food image classification accuracy.
文摘Food production in the countries of South and South-East Asia has shown a general upward trend during the last decade. Despite the considerable increase in population in many of these countries, food production per capita in 1988-90 was significantly higher as compared to 1979-81 figures, the increase being specially marked in such countries as Vietnam, Cambodia, Indonesia, and Malaysia. Available daily calorie supply was adequate to meet the requirement. The overall pattern of food production however has shown little change, with cereal production continuing to account for a predominant part of food production. There is no evidence of a significant uptrend with respect to production of pulses, milk, horticultural products, poultry or meat production in most countries.A uniquc and unfortunate feature of the nutrition situation in South-Asian countries is that the incidence of low birth weight deliveries is as high as 34% (1990), ranging from 25% in Sri Lanka to 50% in Bangladesh (as against less than 7% in the countries of Europe and North America). Even in countries of Africa where the overall food and nutrition situation is worse than in South Asia, the incidence is well below 20%. This is a reflection of the poor state of maternal nutrition in pregnancy.Florid nutritional deficiency diseases have shown a steep decline over the last two decades, but goitre and iron deficiency anaemia continue to be major public health problems, though some headway has been made with regard to the control of the former. Severe forms of growth retardation in children have declined but the majority suffer from mild and moderate forms of growth retardation.Countries of the Region are in varying stages of developmental transition. Among the burgeoning middle classes in some of these countries there are evidences of escalation of degenerative diseases such as diabetes and coronary heart disease. With increasing life expectancy, geriatric nutritlonal problems will demand increasing attention
文摘The detection and recognition of food pictures has become an emerging application field of computer vision. However, due to the small differences between the categories of food pictures and the large differences within the categories, there are problems such as missed inspections and false inspections in the detection and recognition process. Aiming at the existing problems, an <span>improved YOLOv3 model of Asian food detection method is proposed.</span> Firstly, increase the top-down fusion path to form a circular fusion, making full use of shallow and deep features. Secondly, introduce the convolution residual <span>module to replace the ordinary convolution layer to increase the gradient</span> cor<span>relation and non-linearity of the network. Thirdly, introduce the CBAM</span> (Con<span>volutional Block Attention Module) attention mechanism to improve the</span> network’s ability to extract effective features. Finally, CIOU (Complete-IoU) loss is used to improve the convergence efficiency of the model. Experimental results show that the proposed improved model achieves better detection results on the Asian food UECFOOD100 data set.
