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Hi, I'm Mark

ML Engineer — MLOps, ML systems, and building things from first principles

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Future Blog Post

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

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Blog Post number 2

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Blog Post number 1

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Medical Waste Classification using Deep Learning and Convolutional Neural Networks

Published in IEEE IATMSI 2022 (IEEE Xplore) — cited 25 times, 2023

First author. Trained a CNN to 98.4% accuracy for medical-waste classification and deployed it as an interactive TensorFlow.js web application. Multi-class classification of medical waste as part of an automated system to segregate it without human intervention. Cited 25 times.

Recommended citation: M. Verma, A. Kumar and S. Kumar, "Medical Waste Classification using Deep Learning and Convolutional Neural Networks," 2022 IEEE Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI), Gwalior, India, 2022, pp. 1-5, doi: 10.1109/IATMSI56455.2022.10119431. keywords: {Training;Deep learning;Computer vision;Technological innovation;Hospitals;Computational modeling;Transfer learning;Deep Learning;Medical Waste Classification;Transfer Learning;Convolutional Neural Network(CNN)},
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