Abstract:

Object detection in real-time video streams is a critical task with diverse applications ranging from surveillance to autonomous driving. This research paper presents a robust approach leveraging deep learning techniques for real-time object detection. The proposed method utilizes a Convolutional Neural Network (CNN) architecture trained on the Caffe framework, enabling efficient detection of various objects in live video feeds

Description:

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