Food/Non-food Image Classification and Food Categorization using Pre-Trained GoogLeNet Model

Recent past has seen a lot of developments in the field of image-based dietary assessment. Food image classification and recognition are crucial steps for dietary assessment. In the last couple of years, advancements in the deep learning and convolutional neural networks proved to be a boon for the image classification and recognition tasks, specifically for food recognition because of the wide variety of food items. In this paper, we report experiments on food/non-food classification and food recognition using a GoogLeNet model based on deep convolutional neural network. The experiments were conducted on two image datasets created by our own, where the images were collected from existing image datasets, social media, and imaging devices such as smart phone and wearable cameras. Experimental results show a high accuracy of 99.2% on the food/non-food classification and 83.6% on the food category recognition

Strategies to improve the dietary quality of Supplemental Nutrition Assistance Program (SNAP) beneficiaries: an assessment of stakeholder opinions

Objective: To examine the opinions of stakeholders on strategies to improve dietary quality of Supplemental Nutrition Assistance Program (SNAP) participants. Design: Participants answered a thirty-eight-item web-based survey assessing opinions and perceptions of SNAP and programme policy changes. Setting: USA. Subjects: Survey of 522 individuals with stakeholder interest in SNAP, conducted in October through December 2011. Results: The top three barriers to improving dietary quality identified were: (i) unhealthy foods marketed in low-income communities; (ii) the high cost of healthy foods; and (iii) lifestyle challenges faced by low-income individuals. Many respondents (70 %) also disagreed that current SNAP benefit levels were adequate to maintain a healthy diet. Stakeholders believed that vouchers, coupons or monetary incentives for purchasing healthful foods might have the greatest potential for improving the diets of SNAP participants. Many respondents (78 %) agreed that sodas should not be eligible for purchases with SNAP benefits. More than half (55 %) believed retailers could easily implement such restrictions. A majority of respondents (58 %) agreed that stores should stock a minimum quantity of healthful foods in order to be certified as a SNAP retailer, and most respondents (83 %) believed that the US Department of Agriculture should collect data on the foods purchased with SNAP benefits. Conclusions: Results suggest that there is broad stakeholder support for policies that align SNAP purchase eligibility with national public health goals of reducing food insecurity, improving nutrition and preventing obesity

Behavioral and Social Influences on Food Choice

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75438/1/j.1753-4887.1998.tb01732.x.pd

The concept of "compartment allergy": prilocaine injected into different skin layers

We herein present a patient with delayed-type allergic hypersensitivity against prilocaine leading to spreading eczematous dermatitis after subcutaneous injections for local anesthesia with prilocaine. Prilocaine allergy was proven by positive skin testing and subcutaneous provocation, whereas the evaluation of other local anesthetics - among them lidocaine, articaine and mepivacaine - did not exhibit any evidence for cross-reactivity

Big Food, Food Systems, and Global Health

In an article that forms part of the PLoS Medicine series on Big Food, guest editors David Stuckler and Marion Nestle lay out why more examination of the food industry is necessary, and offer three competing views on how public health professionals might engage with Big Food

Food Politics

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