Abstract:

In this difficult progression, the main role of object detection necessitates computer vision that works with both indoor and outdoor classes. This enthusiasm has grown increasingly demanding over the years. Previous approaches to implementation used a single tagging mechanism for object detection. In this context, a multi-label method employing vision and machine learning technology can produce an accurate answer that can be recognized for its efficacy. In the proposed research, we employ classification/clustering strategies to address the system's current issue by shortening the time it takes to recognize many items while minimizing temporal complexity. The visualization employed to help blind individuals can recognize items on its own that are right in front of them. Research and reverence confused the development of these algorithms based on machine learning for vision impaired people to help develop precise navigation in both indoor and outdoor settings

Description:

Machine learning, Deep Learning, Object detection