Please use this identifier to cite or link to this item: https://elibrary.khec.edu.np/handle/123456789/1018
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dc.contributor.advisorEr. Dinesh Gothe-
dc.contributor.authorJenish Prajapati Roji Prajapati Shreeya Shrestha Sumina Awa (770314) (770333) (770342) (770345)-
dc.date.accessioned2025-09-15T12:24:30Z-
dc.date.available2025-09-15T12:24:30Z-
dc.date.issued2025-
dc.identifier.urihttps://elibrary.khec.edu.np/handle/123456789/1018-
dc.description.abstractIn computer vision, identifying and classifying food from photos is a challenging task. Building on our earlier research on Food recognition, we present �Food Ingredient Detection and Recipe Generation from Images� a sophisticated sys tem that can identify dishes from photos, identify their ingredients, and produce recipes that go with them. Through the integration of food classification, in gredient detection, and recipe generation, this project presents a revolutionary method for cuisine recognition. Our system is made to examine photos of various food, identify the ingredients, and then give users comprehensive recipe instruc tions depending on the components found. The system provides an interactive experience that helps food scholars, and chefs learn about cuisine by utilizing deep learning algorithms and a carefully maintained recipe library. By using cutting-edge AI-driven technologies, this breakthrough helps to preserve and ad vance traditional culinary knowledge.-
dc.format.extent81 p-
dc.subjectComputer Vision, Food Classification, Food Recognition, Ingredient Detection, Recipe Generation-
dc.titleFOOD LENS: Food Ingredient Detection & Recipe Generation from Images-
dc.typeReport-
local.college.nameKhwopa Engineering College-
local.degree.departmentDepartment of Computer Engineering-
local.college.batch2077-
local.degree.nameBE Computer-
local.degree.levelBachelor's Degree-
local.item.accessionnumberD.1557-
Appears in Collections:PU Computer Report

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