• Vinod Kumar M
• Anupama K C
• Dr.R.Nagaraja

Object Detection is a important application in Computer Vision technology, which is characterized by the extraction of features from the given input image. With the advances in deep learning technology it has gained a drastic speed to it due to its accuracy and performance enhancement. The proposed work aims at achieving the accuracy and classification of the objects in a given image. The work also gives the features of usages with the detected classes by predicting the event or idea about the area surrounding the image. The major problem of object detection is due to the object detection model depend on the other computer vision technologies. The model is developed with completely the using deep learning approach. The model is trained using publically available dataset COCO, which is consisting of common daily images. The resulting system detects the objects of various class and predicts the event based on the objects class present. The available models use deep learning for object detection but the accuracy decreases with comparatively.

COCO, Deep Learning, system, feature selection, machine learning.

"Object Detection, Classification and Event Detection Using YOLO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.662-666, June-2019, Available :http://www.jetir.org/papers/JETIR1906E49.pdf

"Object Detection, Classification and Event Detection Using YOLO", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp662-666, June-2019, Available at : http://www.jetir.org/papers/JETIR1906E49.pdf