Food recognition using neural network classifier and multiple hypotheses image segmentation

ABSTRACT

This paper proposes the multiple-hypotheses image segmentation and feed-forward neural network classifier for food recognition to improve the performance. Initially, the food or meal image is given as input. Then, the segmentation is applied to identify the regions, where a particular food item is located using salient region detection, multi-scale segmentation, and fast rejection. Then, the features of every food item are extracted by the global feature and local feature extraction. After the features are obtained, the classification is performed for each segmented region using a feed-forward neural network model. Finally, the calorie value is computed with the aid of (i) food volume and (ii) calorie and nutrition measure based on mass value. The experimental results and performance evaluation are validated. The outcome of the proposed method attains 0.947 for Macro Average Accuracy (MAA) and 0.959 for Standard Accuracy (SA), which provides better classification performance.     

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Extracting Light from Polymer Light‐Emitting Diodes Using Stamped Bragg Gratings

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Recovery of gold cyanide using inherently conducting polymers

Removal of gold from basic solutions containing [Au(CN)₂]^? has been demonstrated using the inherently conducting polymer polypyrrole. Polymers containing sulfonated aromatic dopants have been found to display a significant ability to remove gold from such solutions. Experiments performed in solutions containing both gold and copper cyanide complexes indicate that the recovery process is not highly selective. However, the polypyrroles used display significantly faster rates of gold recovery than activated carbon. © 2003 Society of Chemical Industry     

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菱镁矿固硫特性的理论分析

对菱镁矿在固体燃料燃烧过程中的固硫特性进行了理论研究，所得结论对进一步将菱镁矿作为固体燃料燃烧过程中的固硫剂具有非常重要的意义。     

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