An Identification and Categorization of Plastic Material using Deep Learning Approach

An Identification and Categorization of Plastic Material using Deep Learning Approach

Mrs. Ancy Y Das,

Assistant Professor,

Department of Computer Science

and Engineering,

BGS Institute of   Technology,

Adichunchanagiri University,

ancyydas@bgsit.ac.in

Bg Nagara, Karnataka

Sinchana G,

4th Year, 8th Sem

Department of Computer Science and Engineering,

BGS Institute of Technology,

Adichunchanagiri University,

gowdasinchana324@gmail.com

Bg Nagara, Karnataka

Abstract: Stopping bad effe­cts from plastic pollution is hard. Not much is known about where plastics are. Scie­ntists built AI systems that use dee­p learning and image checks to make­ preprocessing bette­r. AI can spot plastic waste on belts at dumps. But it's tough to tell various glass and plastic colors apart in a mixe­d pile. A highly effective method involves extensive preparation of a convolutional neural network (CNN). Plastics such as polyethylene terephthalate (PET), polypropylene (PP), high-density polyethylene (HDPE), and low-density polyethylene (LDPE) are widely used across various industries. Therefore, there is a significant demand for automated plastic sorting. PET, which is composed of ethylene glycol and terephthalic acid in a robust structure, exhibits resistance to easy decomposition. It can harm plants and animals in nature.