Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Diet-related chronic diseases severely affect personal and global health. Hover, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images.  propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods re evaluated on a database of over 1600 manually annotated im- ages. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions.
['Joachim Dehais', 'Marios Anthimopoulos', 'Stavroula G. Mougiakakou']
I am writing a research paper on a idea Dish Detection and Segmentation for Dietary Assessment on Smartphones
[{"from": "human", "value": "I am writing a research paper on a idea Dish Detection and Segmentation for Dietary Assessment on Smartphones"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Diet-related chronic diseases severely affect personal and global health. Hover, managing or treating these diseases currently requires long training and high personal involvement to succeed. Computer vision systems could assist with the assessment of diet by detecting and recognizing different foods and their portions in images.  propose novel methods for detecting a dish in an image and segmenting its contents with and without user interaction. All methods re evaluated on a database of over 1600 manually annotated im- ages. The dish detection scored an average of 99% accuracy with a .2s/image run time, while the automatic and semi-automatic dish segmentation methods reached average accuracies of 88% and 91% respectively, with an average run time of .5s/image, outperforming competing solutions."}]