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dc.contributor.authorAkshat Mittal, 19SCSE1010884
dc.contributor.authorMonisha Mandal, 19SCSE1180033
dc.date.accessioned2024-09-18T04:35:58Z
dc.date.available2024-09-18T04:35:58Z
dc.date.issued2023-05
dc.identifier.urihttp://10.10.11.6/handle/1/18072
dc.descriptionSCHOOL OF COMPUTING SCIENCE AND ENGINEERING DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING / DEPARTMENT OF COMPUTER APPLICATION GALGOTIAS UNIVERSITY, GREATER NOIDAen_US
dc.description.abstractWater pollution is a significant environmental problem that affects the health and wellbeing of humans and wildlife. Garbage in rivers is a primary contributor to water pollution and poses a significant threat to marine life. Detecting and managing garbage in rivers is crucial for effective pollution management and conservation efforts. Traditional methods of detecting trash in rivers are often labor-intensive and time consuming, making it challenging to identify and manage garbage in a timely manner. However, recent advances in deep learning algorithms and the PyTorch framework have shown promise in automating the detection and management of garbage in rivers.en_US
dc.language.isoen_USen_US
dc.publisherGalgotias Universityen_US
dc.subjectAutomatic Detectionen_US
dc.subjectDeep Learningen_US
dc.subjectGarbageen_US
dc.titleAutomatic Detection of Garbage in Rivers using Deep Learningen_US
dc.typeTechnical Reporten_US


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