6521be08-4a22-4715-942c-5c3c13503c7e beie director@blueeyesintelligence.org 10.35940/ijitee.F8804.0410621 10.1109/TVCG.2017.2744683Bilal, A. Jourabloo, M. Ye, X. Liu, and L. Ren. Do Convolutional Neural Networks Learn Class Hierarchy? IEEE Transactions on Visualization and Computer Graphics, 24(1):152-162, Jan. 2018.10.1145/3334480.3382839M. Carney, B. Webster, I. Alvarado, K. Phillips, N. Howell, J. Griffith, J. Jongejan, A. Pitaru, and A. Chen. Teachable Machine: Approachable Web-Based Tool for Exploring Machine Learning Classification. In Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, CHI '20. ACM, Honolulu, HI, USA, 2020.A. Karpathy. CS231n Convolutional Neural Networks for Visual Recognition, 201610.1109/TVCG.2018.2864500M. Kahng, N. Thorat, D. H. Chau, F. B. Viegas, and M. Wattenberg. GANLab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation. IEEE Transactions on Visualization and Computer Graphics, 25(1):310-320, Jan. 2019.J. Yosinski, J. Clune, A. Nguyen, T. Fuchs, and H. Lipson. Understanding Neural Networks Through Deep Visualization. In ICML Deep Learning Workshop, 201510.1109/TVCG.2017.2744718M. Kahng, P. Y. Andrews, A. Kalro, and D. H. Chau. ActiVis: Visual Exploration of Industry-Scale Deep Neural Network Models. IEEE Transactions on Visualization and Computer Graphics, 24(1):88-97, Jan. 2018.https://cs231n.github.io/convolutional-networks/https://www.analyticsvidhya.com/blog/2020/02/learn-image-classification-cnn-convolutional-neural-networks-3-datasets/https://towardsdatascience.com/understanding-cnn-convolutional-neural- network-69fd626ee7d4https://medium.com/@birdortyedi_23820/deep-learning-lab-episode-2-cifar- 10-631aea84f11e10.1016/j.patcog.2017.10.013J. Gu, Z. Wang, J. Kuen, L. Ma, A. Shahroudy, B. Shuai, T. Liu, X. Wang, G. Wang, J. Cai, and T. Chen. Recent advances in convolutional neural networks. Pattern Recognition, 77:354-377, May 2018.International Journal of Information TechnologyHamid112251201410.1007/s41870-018-0225-xWavelet neural network model for network intrusion detection systemHamid, Y., Shah, F.A. and Sugumaram, M. (2014), "Wavelet neural network model for network intrusion detection system", International Journal of Information Technology, Vol. 11 No. 2, pp. 251-26310.1108/IJPCC-05-2020-0036G Sreeram , S Pradeep, K SrinivasRao , B.Deevan Raju , Parveen Nikhat , " Moving ridge neuronal espionage network simulation for reticulum invasion sensing". International Journal of Pervasive Computing and Communications.https://doi.org/10.1108/IJPCC-05-2020-0036E. Stevens, L. Antiga, and T. Viehmann. Deep Learning with PyTorch. O'Reilly Media, 2019.J. Yosinski, J. Clune, A. Nguyen, T. Fuchs, and H. Lipson. Understanding Neural Networks Through Deep Visualization. In ICML Deep Learning Workshop, 2015.10.2174/2213275911666181025143029Aman Dureja, Payal Pahwa, "Analysis of Non-Linear Activation Functions for Classification Tasks Using Convolutional Neural Networks", Recent Advances in Computer Science , Vol 2, Issue 3, 2019 ,PP-156-161https://missinglink.ai/guides/neural-network-concepts/7-types-neural-network-activation-functions-right/