The purpose of this paper is to develop a computer vision model using deep learning technique that can detect the
different kind of waste. Waste disposal and its management are considered as an essential part in maintaining cleanliness in the
cities. Waste management becomes easy if segregation of different kind of waste happens at initial level. The paper begins with
analyzing advantages and disadvantages of existing smart bins that mainly focus on weight of the waste inside them. There are
few proposed framework for waste segregation but a better and a strong model can be developed using deep learning. The goal is
to come up with an optimized object detection architecture may be used for segregating three different kinds of waste that are
normally generated, that is plastic, paper and wet waste in real-time with better accuracy and lesser time taken for generating the
inference.
