Implementing object Detection for Real-World Applications

 The advent of deep learning has enabled the development of powerful AI models that are being used in fields such as medicine, surveillance monitoring, optimizing manufacturing processes, allowing robots to navigate their environment, chatbots, and much more. These applications are only made possible because of the enormous research in the fields of Neural networks and deep learning. In this paper, I’ll be discussing a branch of Neural Networks called Convolution Neural Network (CNN), and how they are used for object detection tasks for detecting and classifying objects in an image. I’ll also discuss a popular object detection framework called Single Shot Multibox Detector (SSD) and implement it in my web application project which allows users to detect objects in images and search for images based on the presence of objects. The main aim of the project was to allow easy access to perform detections with a few clicks.