Evaluating the Performance of ResNet Model Based on Image Recognition

In this study, we have used two different Datasets to evaluate the performance of ResNet model. First dataset consists of images about healthcare data while second dataset consists of malware and benign _les. We performed experiments to predict cancer on the first dataset and detect malware on the second dataset. ResNet models i.e. Resnet18, ResNet50, ResNet101 and ResNet152 are investigated and tested which belong to Microsoft. The neural networks system has been turned out to be _t for approximating any ceaseless capacity, and all the more as of late profound neural systems (DNNs) have been observed to be viable in a few spaces, going from PC vision, speech recognition, to text processing. The purpose of this paper is to make recommendations prediction of the cancer disease adopting Neural networks and detecting the malware _les through the same ResNet model. We evaluated the performance of ResNet model on two different datasets.