Aim: To enhance the accuracy in human detection and human counting using a novel Convolutional Neural Network (CNN) over Support Vector Machine (SVM) algorithm. Materials and Methods: This research study contains two groups, group one is novel convolutional neural network and group two is support vector machine algorithm. Each group consists of a sample size of 10 and the study parameters include alpha value 0.05, beta value 0.2, and the power value 0.8. Their accuracies are also compared with each other using different sample sizes. Results: The novel convolutional neural network is 94.302 more accurate than the support vector machine algorithm of 784.302% in human detection and human counting. Conclusion: The CNN model is significantly better than the SVM in detecting and counting humans. It can be also considered as a better option for human detection and counting the total number of humans in a frame.