I have Used Convolutional Neural Network in my model. Convolutional Neural Network (CNN) is a Deep Learning based algorithm that can take images as input, assign classes for the objects in the ima ...

The experimental results show that the optimized Cascade R-CNN object detection algorithm has the best comprehensive performance, and the average accuracy (AP 0.5) reaches 95.5%, which is 3.5% better ...

Pendeteksian objek menghasilkan akurasi model sebesar 95.63%, model ini digunakan pada file video dan berhasil mendeteksi objek rambu lalu lintas dengan baik. Kata kunci: Object Detection, Deep ...

Car damage detection systems have become very significant in various daily activities, like the insurance claims process, accident reporting systems, or a documented write up of the various damages a ...

Now let us discuss what are the different popular algorithms used for object detection that are based on the CNN model. First, we will come to know about three popular models – R-CNN, Fast-RCNN and ...

The mainstream object detection algorithms are based on convolution neural networks (CNN), which are one-stage and two-stage detections, using different feature extraction methods.

The proposed model has four main steps, namely, preprocessing, segmentation, feature extraction, and classification. Initially, the input SAR image is pre-processed using a histogram equalization ...