Papers › Waste Classification Algorithm
Waste Classification Algorithm
Neha Naveen, Michael Rodrigues, Srjana Srivatsa
Waste sorting is a major environmental problem. Many have a hard time determining whether waste is organic, meaning food or natural material. Versus recyclable, which are able to be processed and used again. Computer Vision may be used to combat this problem. Our idea is to build and utilize a Convolutional Neural Network (CNN) to classify recyclable and organic waste. We use the Pytorch Machine Learning Library in our CNN. The model uses a simple CNN model with binary cross entropy to classify through images from our dataset as recyclable (R) or organic (O). The model is about 80-90% successful in its final state. In the majority of cases, it can quickly and successfully determine if an object is recyclable or organic.
Code
No code repository is listed for this paper in the archive or in Syntology's graph.
Code Syntology ran Syntology
Not run by Syntology. Nothing on this page verifies that the listed code works.
Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
No leaderboard rows for this paper in the archive.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections