A) Theory (4 papers)
J. Schmidhuber, "Deep learning in neural networks: An overview, Neural Networks", pages 85–117, January 2015.
W. Liu, Z.Wang, X.Liu, N. Zeng, Y. Liuc, F. Alsaadid, "A survey of deep neural network architectures and their applications", Neurocomputing, Volume 234, pages 11–26, April 2017.
J. Gu, Z. Wang, J. Kuen, L. Ma, A. Shahroudy, B. Shuai, T. Liu, X. Wang, "Recent advances in convolutional neural networks", Pattern Recognition, Volume 77, pages 354–377. 2018.
H. Yi, S. Shiyu, D. Xiusheng, C. Zhigang, "A study on deep neural networks framework", IMCEC 2016, pages 1519–1522, 2016.
B) Applications (25 papers)
General (1 paper)
S. Dong, P. Wang, K. Abbas, “A survey on deep learning and its applications”, Computer Science Review, Volume 40, May 2021.
Computer Science (1 paper)
P. Dixit, S. Silakari, “Deep Learning Algorithms for Cybersecurity Applications: A Technological and Status Review”, Computer Science Review, Volume 39, February 2021.
Computer Vision (23 papers)
3.1 2D Computer Vision (14 papers)
Image Enhancement (2 papers)
Y. Wang, W. Xie, H. Liu, “Low-light image enhancement based on deep learning: a survey”, SPIE Optical Engineering, 2022.
Q. Zhao, G. Li, B. He, R. She, "Deep Learning for Low-light Vision: A Comprehensive Survey", IEEE Transactions on Neural Networks and Learning Systems, 2025.
Image Segmentation (1 paper)
S. Minaee, Y. Boykov, F. Porikli, A. J. Plaza, N. Kehtarnavaz, D. Terzopoulos, "Image Segmentation using Deep Learning: A Survey", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021.
Semantic Segmentation (3 papers)
A. Garcia-Garcia, S. Orts-Escolano, S. Oprea, V. Villena-Martinez, P. Martinez-Gonzalez, J. Garcia-Rodriguez, "A Review on Deep Learning Techniques Applied to Semantic Segmentation", Preprint, 2017.
A. Garcia-Garcia, S. Orts-Escolano, S. Oprea, V. Villena-Martinez, P. Martinez-Gonzalez, J. Garcia-Rodriguez, "A survey on deep learning techniques for image and video semantic segmentation", Applied Soft Computing, Volume 70, pages 41-65, 2018.
Y. Guo, Y. Liu, T. Georgiou, M. Lew, "A review of semantic segmentation using deep neural networks", International Journal of Multimedia Information Retrieval, 2017.
Face Recognition (1 paper)
M. Wang, W. Deng, "Deep Face Recognition: A Survey", Preprint, February 2019.
Image Recognition (1 paper)
K. Ohri, M. Kumar, “Review on self-supervised image recognition using deep neural networks”, Knowledge-Based Systems, Volume 224, July 2021.
Pose Estimation (7 papers)
Y. Chen, Y. Tian, M. He, " Monocular human pose estimation: A survey of deep learning-based methods", CVIU 2020, 2020.
R. Gadhiya, N. Kalani, "Analysis of Deep Learning Based Pose Estimation Techniques for Locating Landmarks on Human Body Parts", International Conference on Circuits, Controls and Communications, CCUBE 2021, pages 1-4, 2021.
M. Gamra, M. Akhloufi, "A Review Of Deep Learning Techniques For 2D And 3D Human Pose Estimation", Image and Vision Computing, 2021.
W. Lu, Q. Bao, Y. Sun, T. Mei, "Recent Advances of Monocular 2D and 3D Human Pose Estimation: A Deep Learning Perspective", ACM Computing Surveys, 2022.
G. Lan, Y. Wu, F. Hu and Q. Hao, "Vision-based Human Pose Estimation via Deep Learning: A Survey", IEEE Transactions on Human-Machine Systems, Volume 53, No. 1, pages 253-268, February 2023.
C. Zheng, W. Wu, C. Chen, T. Yang, S. Zhu, J. Shen, N. Kehtarnavaz, “Deep Learning-based Human Pose Estimation: A Survey”, ACM Computing Surveys, Volume 56, Issue 1 , pages 1-37, 2023.
N. Fisal, A. Fathalla, D. Elmanakhly, A. Salah, “Reported Challenges in Deep Learning-Based Human Pose Estimation: A Systematic Review”, IEEE Access, 2025
3.2 2D+t Computer Vision (7 papers)
Background/Foreground Separation (1 paper)
T. Bouwmans, S. Javed, M. Sultana, S. Jung, “Deep Neural Network Concepts in Background Subtraction: A Systematic Review and A Comparative Evaluation”, Neural Networks, 2019.
Person Detection and Tracking (3 papers)
A. Brunettia, D. Buongiorno, G. Trotta, V. Bevilacqua, "Computer vision and deep learning techniques for pedestrian detection and tracking: A survey", Neurocomputing, July 2018.
L. Chen, S. Lin, X. Lu, D. Cao, H. Wu, C. Guo, C. Liu, F. Wang , "Deep Neural Network Based Vehicle and Pedestrian Detection for Autonomous Driving: A Survey", IEEE Transactions on Intelligent Transportation Systems, Volume 22, No. 6, pages 3234-3246, June 2021.
S. Grigorescu, B. Trasnea, T. Cocias, G. Macesanu, "A survey of deep learning techniques for autonomous driving", Journal of Field Robotics, Volume 37, 362-386, 2020.
Person re-identification (2 papers)
D. Wu et al., “Deep learning-based methods for person re-identification: A comprehensive review”, Neurocomputing, February 2019.
B. Lavi, M. Serj, I. Ullah, “Survey on Deep Learning Techniques for Person Re-Identification Task”, Neurocomputing, 2018.
Action Recognition (2 papers)
G. Yao, T. Lei, J. Zhong, “A Review of Convolutional-Neural-Network-based Action Recognition”, Pattern Recognition Letters, pages 14–22, 2019.
J. Wang, Y.Chen, S. Hao, X. Peng, L. Hu, “Deep Learning for Sensor-based Activity Recognition: A Survey”, Pattern Recognition Letters, Volume 119, pages 3-11, March 2019.
Anomaly Detection (1 paper)
M. Sabuhi, M. Zhou, C. Bezemer, P. Musilek, "Applications of Generative Adversarial Networks in Anomaly Detection: A Systematic Literature Review", Preprint, October 2021.