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New system estimates calories in Bangladeshi street food using AI models

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a vision-based system for estimating the calorie content of Bangladeshi street food, addressing a gap in current Western-centric approaches. The study compared five object detection and segmentation models, with YOLO11n achieving the highest detection performance. For calorie prediction, a Random Forest regression model, utilizing geometric features extracted by YOLO11n and a Bangladeshi 5 Taka coin for scale reference, yielded the best results with a mean absolute error of 5.68. AI

IMPACT This research could enable more accurate dietary monitoring and the development of specialized mobile health applications for diverse global cuisines.

RANK_REASON The cluster contains an academic paper detailing a new methodology and comparative study of AI models for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New system estimates calories in Bangladeshi street food using AI models

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The cluster contains an academic paper detailing a new methodology and comparative study of AI models for a specific application. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Aparup Dhar, Antu Das, Pritom Barua, MD Tamim Hossain ·

    Vision-Based Calorie Estimation for Bangladeshi Street Food: A Comparative Study of Detection and Regression Models

    arXiv:2509.01415v2 Announce Type: replace Abstract: With obesity emerging as a major global health concern, accurate calorie estimation systems have become increasingly important for effective dietary management. Current vision-based approaches are inappropriate for Bangladeshi s…

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