Publication Type : Conference Paper
Publisher : 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT)
Source : 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT) (2019)
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2019
Abstract : Object Detection is widely utilized in several applications such as detecting vehicles, face detection, autonomous vehicles and pedestrians on streets. TensorFlow's Object Detection API is a powerful tool that can quickly enable anyone to build and deploy powerful image recognition software. Object detection not solely includes classifying and recognizing objects in an image however additionally localizes those objects and attracts bounding boxes around them. This paper mostly focuses on detecting harmful objects like threatening objects. To ease object detection for threatening objects, we have got Tensor flow Object Detection API to train model and we have used Faster R-CNN algorithm for implementation. The model is built on two classes of threatening Objects. The model is evaluated on test data for the two classes of detecting threatening objects.
Cite this Research Publication : B. N. Krishna Sai and Sasikala T, “Object Detection and Count of Objects in Image using Tensor Flow Object Detection API”, in 2019 International Conference on Smart Systems and Inventive Technology (ICSSIT), 2019.