Open Access
ITM Web Conf.
Volume 43, 2022
The International Conference on Artificial Intelligence and Engineering 2022 (ICAIE’2022)
Article Number 01008
Number of page(s) 6
Published online 14 March 2022
  1. Pralhad Gavali ME, J. Saira Banu PhD, in Deep Learning and Parallel Computing Environment for Bioengineering Systems, 2019. [Google Scholar]
  2. Anna Syberfeldt, Fredrik Vuoluterä, Image Processing based on Deep Neural Networks for Detecting Quality Problems in Paper Bag Production, Procedia CIRP, Volume 93 ,2020, Pages 1224-1229, ISSN 2212-8271. [Google Scholar]
  3. Ajeet Ram Pathak, Manjusha Pandey, Siddharth Rautaray, Application of Deep Learning for Object Detection, Procedia Computer Science, Volume 132, 2018, Pages 1706-1717, ISSN 1877-0509. [CrossRef] [Google Scholar]
  4. Mayur Bhargab Bora, Dinthisrang Daimary, Khwairakpam Amitab, Debdatta Kandar, Handwritten Character Recognition from Images using CNN-ECOC, Procedia Computer Science, Volume 167, 2020, Pages 2403-2409, ISSN 1877-0509. [CrossRef] [Google Scholar]
  5. Pin Wang, En Fan, Peng Wang, Comparative analysis of image classification algorithms based on traditional machine learning and deep learning, Pattern Recognition Letters, Volume 141, 2021, Pages 61-67, ISSN 0167-8655. [CrossRef] [Google Scholar]
  6. Sakshi Indolia, Anil Kumar Goswami, S.P. Mishra, Pooja Asopa, Conceptual Understanding of Convolutional Neural Network- A Deep Learning Approach, Procedia Computer Science, Volume 132, 2018, Pages 679-688, ISSN 1877-0509. [CrossRef] [Google Scholar]
  7. U.K. Lopes, J.F. Valiati, Pre-trained convolutional neural networks as feature extractors for tuberculosis detection, Computers in Biology and Medicine, Volume 89,2017, Pages 135-143, ISSN 0010-4825. [CrossRef] [Google Scholar]
  8. Chollet, F. (2015) keras, GitHub. [Google Scholar]
  9. Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Rafal Jozefowicz, Yangqing Jia, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Mike Schuster, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng. TensorFlow: Large-scale machine learning on heterogeneous systems, 2015. Software available from [Google Scholar]
  10. J Praveen Gujjar, R Prasanna Kumar H, Niranjan N. Chiplunkar, Image Classification and Prediction using Transfer Learning in Colab Notebook, Global Transitions Proceedings, 2021, ISSN 2666-285X. [Google Scholar]
  11. Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens. 2015. Rethinking the Inception Architecture for Computer Vision. [Google Scholar]
  12. Deng J, Dong W, Socher R, Li L-J, Li K, Fei-Fei L. Imagenet: A large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition. 2009. p. 248–55. [CrossRef] [Google Scholar]
  13. G. Hinton, O. Vinyals, and J. Dean. Distilling the knowledge in a neural network. In NIPS, 2014. [Google Scholar]
  14. Karen Simonyan and Andrew Zisserman. 2015. Very Deep Convolutional Networks for large-scale Image Recognition. [Google Scholar]
  15. François Chollet. 2017. Xception: Deep Learning with Depthwise Separable Convolutions. [Google Scholar]
  16. Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen. Google [Google Scholar]
  17. Inc. 2019. MobileNetV2: Inverted Residuals and Linear Bottlenecks. [Google Scholar]
  18. T. Alshalali and D. Josyula, “Fine-Tuning of Pre-Trained Deep Learning Models with Extreme Learning Machine,” 2018 International Conference on Computational Science and Computational Intelligence (CSCI), 2018, pp. 469-473. [Google Scholar]
  19. Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun. Microsoft Research. 2015. Deep Residual Learning for Image Recognition. [Google Scholar]
  20. T. E. de Campos, B. R. Babu and M. Varma. Character recognition in natural images. In Proceedings of the International Conference on Computer Vision Theory and Applications (VISAPP), Lisbon, Portugal, February 2009. [Google Scholar]
  21. Qi Xu, Ming Zhang, Zonghua Gu, Gang Pan, Overfitting remedy by sparsifying regularization on fully-connected layers of CNNs, Neurocomputing, Volume 328, 2019, Pages 69-74, ISSN 0925-2312. [CrossRef] [Google Scholar]
  22. B. Biswal, Geetha Pavani P, Prasanna T, Prakash Kumar karn, Robust segmentation of exudates from retinal surface using M-CapsNet via EM routing, Biomedical Signal Processing and Control, Volume 68, 2021, 102770, ISSN 1746-8094. [CrossRef] [Google Scholar]
  23. Dua, D. and Graff, C. (2019). UCI Machine Learning Repository []. Irvine, CA: University of California, School of Information and Computer Science. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.