Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Volume - 13 | Issue-1
Aim: To improve the precision rate in Object Detection and Classification and to identify the objects based on Novel Region-Based Convolutional Neural Networks (RCNN) and Support Vector Machine algorithms. Materials and Methods: Classification is performed by Novel Region-Based Convolutional Neural Networks (N=10) over Support Vector Machine (N=10). The sample size is calculated using GPower with pretest power as 0.8 and alpha 0.05. Result: Mean accuracy of Novel Region-Based Convolutional Neural Networks (96.9%) is high compared to Support Vector Machine (90.00%). The significance value for accuracy and loss is 0.339 (p>0.05). Conclusion: The mean accuracy of the object detection and classification in Novel Region-Based Convolutional Neural Networks (RCNN) is better than the Support Vector Machine algorithm.