Deep-Segregation of Plastic (DSP): Segregation of Plastic and Non-Plastic using Deep learning
About DSP
The aim of the project is to develop an engine which uses modern artificial intelligence approach, deep learning and computer vision to automatically classify the waste into plastic or non-plastic. This is just a proof-of-concept model. We have evaluate the performance of deep learning approaches such as CNN and CapsNet on both the publically avilable and real-time data sets.
Demo
Team Members
Sreelakshmi K, Akarsh S, Vinayakumar R and K. P. Soman
Sreelakshmi K is a Mtech Student in the Computational Engineering & Networking, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India since July 2018. She has received Btech from Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India. Her research interests are machine learning, deep learning, signal and image processing.
Akarsh S is a Mtech Student in the Computational Engineering & Networking, Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India since July 2017. He has received Btech from Amrita School of Engineering, Coimbatore, Amrita Vishwa Vidyapeetham, India. His research interests are machine learning, deep learning, cyber security, signal and image processing.
References
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Sreelakshmi K, Vinayakumar R and Soman KP, Deep-Segregation of Plastic (DSP): Segregation of Plastic and Non-Plastic using Deep learning. In Big Data Recommender Systems: Recent Trends and Advances, Institution of Engineering and Technology (IET) [Book chapter - In Press]
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Sreelakshmi K, Akarsh S, Vinayakumar R and Soman KP, Capsule Neural Networks and Visualization for Segregation of Plastic andNon-Plastic Wastes ### Best paper award in 2019 International Conference on Advanced Computing & Communication Systems (ICACCS)
Hello All, I am Sreelakshmi, happy to share that I have presented my paper titled “Capsule Neural Networks and Visualization for Segregation of Plastic andNon-Plastic Wastes” in ICACCS conference held at Sri Eshwar College of Engineering, Coimbatore. Thanks to all my coauthors: Akarsh S, Vinayakumar R and Soman KP.
Support or Contact: The data set and code is publically avilable for further research
ammaslakshmy[At]gmail.com for the complete code, data set and its experiments