Review on Images Based on Object Detection using Deep Belief Networks

Navdeep Singh, Er. Varinder Kaur Attri


This paper represents the object detection which has been one of the hottest issues in the field of remote sensing image analysis. It is of vital importance for object dynamic surveillance and other applications. So far, object detection has been widely researched. It shows an efficient coarse object locating method based on a saliency mechanism. The method could avoid an exhaustive search across the image and generate a small number of bounding boxes. After that, the trained DBN is used for feature extraction and classification on sub-images. The general purpose of this document is actually to research the a variety of strategies based on object detection and it also demonstrate the accuracy and efficiency of object detection framework using a saliency prior and DBNs for remote sensing images.

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