Accès libre

Deep Learning Algorithms for Efficient Recognition in Biometric Image Classification

  
17 mars 2025
À propos de cet article

Citez
Télécharger la couverture

[1] Li, Y. (2022, January). Research and application of deep learning in image recognition. In 2022 IEEE 2nd international conference on power, electronics and computer applications (ICPECA) (pp. 994-999). IEEE. Li Y. ( 2022 , January ). Research and application of deep learning in image recognition . In 2022 IEEE 2nd international conference on power, electronics and computer applications (ICPECA) (pp. 994 - 999 ). IEEE . Search in Google Scholar

[2] Wu, M., & Chen, L. (2015, November). Image recognition based on deep learning. In 2015 Chinese automation congress (CAC) (pp. 542-546). IEEE. Wu M. Chen L. ( 2015 , November ). Image recognition based on deep learning . In 2015 Chinese automation congress (CAC) (pp. 542 - 546 ). IEEE . Search in Google Scholar

[3] Kaur, N. (2021, March). A study of biometric identification and verification system. In 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 60-64). IEEE. Kaur N. ( 2021 , March ). A study of biometric identification and verification system . In 2021 International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE) (pp. 60 - 64 ). IEEE . Search in Google Scholar

[4] Drozdowski, P., Rathgeb, C., & Busch, C. (2019). Computational workload in biometric identification systems: An overview. IET Biometrics, 8(6), 351-368. Drozdowski P. Rathgeb C. Busch C. ( 2019 ). Computational workload in biometric identification systems: An overview . IET Biometrics , 8 ( 6 ), 351 - 368 . Search in Google Scholar

[5] Chen, C., Li, O., Tao, D., Barnett, A., Rudin, C., & Su, J. K. (2019). This looks like that: deep learning for interpretable image recognition. Advances in neural information processing systems, 32. Chen C. Li O. Tao D. Barnett A. Rudin C. Su J. K. ( 2019 ). This looks like that: deep learning for interpretable image recognition . Advances in neural information processing systems , 32 . Search in Google Scholar

[6] Paterakis, N. G., Mocanu, E., Gibescu, M., Stappers, B., & van Alst, W. (2017, September). Deep learning versus traditional machine learning methods for aggregated energy demand prediction. In 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) (pp. 1-6). IEEE. Paterakis N. G. Mocanu E. Gibescu M. Stappers B. van Alst W. ( 2017 , September ). Deep learning versus traditional machine learning methods for aggregated energy demand prediction . In 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe) (pp. 1 - 6 ). IEEE . Search in Google Scholar

[7] Çayir, A., Yenidoğan, I., & Dağ, H. (2018, September). Feature extraction based on deep learning for some traditional machine learning methods. In 2018 3rd International conference on computer science and engineering (UBMK) (pp. 494-497). IEEE. Çayir A. Yenidoğan I. Dağ H. ( 2018 , September ). Feature extraction based on deep learning for some traditional machine learning methods . In 2018 3rd International conference on computer science and engineering (UBMK) (pp. 494 - 497 ). IEEE . Search in Google Scholar

[8] Lai, Y. (2019, October). A comparison of traditional machine learning and deep learning in image recognition. In Journal of Physics: Conference Series (Vol. 1314, No. 1, p. 012148). IOP Publishing. Lai Y. ( 2019 , October ). A comparison of traditional machine learning and deep learning in image recognition . In Journal of Physics: Conference Series (Vol. 1314 , No. 1 , p. 012148 ). IOP Publishing . Search in Google Scholar

[9] Kamath, C. N., Bukhari, S. S., & Dengel, A. (2018, August). Comparative study between traditional machine learning and deep learning approaches for text classification. In Proceedings of the ACM Symposium on Document Engineering 2018 (pp. 1-11). Kamath C. N. Bukhari S. S. Dengel A. ( 2018 , August ). Comparative study between traditional machine learning and deep learning approaches for text classification . In Proceedings of the ACM Symposium on Document Engineering 2018 (pp. 1 - 11 ). Search in Google Scholar

[10] Chiroma, H. (2021). Deep learning algorithms based fingerprint authentication: systematic literature review. Journal of Artificial Intelligence and Systems, 3(1), 157-197. Chiroma H. ( 2021 ). Deep learning algorithms based fingerprint authentication: systematic literature review . Journal of Artificial Intelligence and Systems , 3 ( 1 ), 157 - 197 . Search in Google Scholar

[11] Al-Waisy, A. S., Al-Fahdawi, S., & Qahwaji, R. (2020). A multi-biometric face recognition system based on multimodal deep learning representations. In Deep Learning in Computer Vision (pp. 89-126). CRC Press. Al-Waisy A. S. Al-Fahdawi S. Qahwaji R. ( 2020 ). A multi-biometric face recognition system based on multimodal deep learning representations . In Deep Learning in Computer Vision (pp. 89 - 126 ). CRC Press . Search in Google Scholar

[12] Jia, X. (2017, May). Image recognition method based on deep learning. In 2017 29th Chinese control and decision conference (CCDC) (pp. 4730-4735). IEEE. Jia X. ( 2017 , May ). Image recognition method based on deep learning . In 2017 29th Chinese control and decision conference (CCDC) (pp. 4730 - 4735 ). IEEE . Search in Google Scholar

[13] Jin, L., & Liang, H. (2017, June). Deep learning for underwater image recognition in small sample size situations. In OCEANS 2017-Aberdeen (pp. 1-4). IEEE. Jin L. Liang H. ( 2017 , June ). Deep learning for underwater image recognition in small sample size situations . In OCEANS 2017-Aberdeen (pp. 1 - 4 ). IEEE . Search in Google Scholar

[14] Sundararajan, K., & Woodard, D. L. (2018). Deep learning for biometrics: A survey. ACM Computing Surveys (CSUR), 51(3), 1-34. Sundararajan K. Woodard D. L. ( 2018 ). Deep learning for biometrics: A survey . ACM Computing Surveys (CSUR) , 51 ( 3 ), 1 - 34 . Search in Google Scholar

[15] Vatsa, M., Singh, R., & Majumdar, A. (Eds.). (2018). Deep learning in biometrics. CRC Press. Vatsa M. Singh R. Majumdar A. (Eds.). ( 2018 ). Deep learning in biometrics . CRC Press . Search in Google Scholar

[16] Chowdhury, A. M., & Imtiaz, M. H. (2022). Contactless fingerprint recognition using deep learning—a systematic review. Journal of Cybersecurity and Privacy, 2(3), 714-730. Chowdhury A. M. Imtiaz M. H. ( 2022 ). Contactless fingerprint recognition using deep learning—a systematic review . Journal of Cybersecurity and Privacy , 2 ( 3 ), 714 - 730 . Search in Google Scholar

[17] Bhanu, B., & Kumar, A. (Eds.). (2017). Deep learning for biometrics (Vol. 7). Cham: Springer. Bhanu B. Kumar A. (Eds.). ( 2017 ). Deep learning for biometrics (Vol. 7 ). Cham: Springer . Search in Google Scholar

[18] Finizola, J. S., Targino, J. M., Teodoro, F. G., & Lima, C. A. (2019, July). Comparative study between deep face, autoencoder and traditional machine learning techniques aiming at biometric facial recognition. In 2019 International Joint Conference on neural networks (IJCNN) (pp. 1-8). IEEE. Finizola J. S. Targino J. M. Teodoro F. G. Lima C. A. ( 2019 , July ). Comparative study between deep face, autoencoder and traditional machine learning techniques aiming at biometric facial recognition . In 2019 International Joint Conference on neural networks (IJCNN) (pp. 1 - 8 ). IEEE . Search in Google Scholar

[19] Abinaya, R., Maguluri, L. P., Narayana, S., & Syamala, M. (2020). A novel biometric approach for facial image recognition using deep learning techniques. International Journal of Advanced Research in Engineering and Technology, 11(9). Abinaya R. Maguluri L. P. Narayana S. Syamala M. ( 2020 ). A novel biometric approach for facial image recognition using deep learning techniques . International Journal of Advanced Research in Engineering and Technology , 11 ( 9 . Search in Google Scholar

[20] Mehraj, H., & Mir, A. H. (2021). A survey of biometric recognition using deep learning. EAI Endorsed Transactions on Energy Web, 8(33), e6-e6. Mehraj H. Mir A. H. ( 2021 ). A survey of biometric recognition using deep learning . EAI Endorsed Transactions on Energy Web , 8 ( 33 ), e6 - e6 . Search in Google Scholar

[21] Zulfiqar, M., Syed, F., Khan, M. J., & Khurshid, K. (2019, July). Deep face recognition for biometric authentication. In 2019 international conference on electrical, communication, and computer engineering (ICECCE) (pp. 1-6). IEEE. Zulfiqar M. Syed F. Khan M. J. Khurshid K. ( 2019 , July ). Deep face recognition for biometric authentication . In 2019 international conference on electrical, communication, and computer engineering (ICECCE) (pp. 1 - 6 ). IEEE . Search in Google Scholar

[22] Ortiz, N., Hernández, R. D., Jimenez, R., Mauledeoux, M., & Avilés, O. (2018). Survey of biometric pattern recognition via machine learning techniques. Contemporary Engineering Sciences, 11(34), 1677-1694. Ortiz N. Hernández R. D. Jimenez R. Mauledeoux M. Avilés O. ( 2018 ). Survey of biometric pattern recognition via machine learning techniques . Contemporary Engineering Sciences , 11 ( 34 ), 1677 - 1694 . Search in Google Scholar

[23] Singhal, N., Ganganwar, V., Yadav, M., Chauhan, A., Jakhar, M., & Sharma, K. (2021). Comparative study of machine learning and deep learning algorithm for face recognition. Jordanian Journal of Computers and Information Technology, 7(3). Singhal N. Ganganwar V. Yadav M. Chauhan A. Jakhar M. Sharma K. ( 2021 ). Comparative study of machine learning and deep learning algorithm for face recognition . Jordanian Journal of Computers and Information Technology , 7 ( 3 . Search in Google Scholar

[24] Selitskaya, N., Sielicki, S., Jakaite, L., Schetinin, V., Evans, F., Conrad, M., & Sant, P. (2020). Deep learning for biometric face recognition: experimental study on benchmark data sets. Deep Biometrics, 71-97. Selitskaya N. Sielicki S. Jakaite L. Schetinin V. Evans F. Conrad M. Sant P. ( 2020 ). Deep learning for biometric face recognition: experimental study on benchmark data sets . Deep Biometrics , 71 - 97 . Search in Google Scholar

[25] Medjahed, C., Rahmoun, A., Charrier, C., & Mezzoudj, F. (2022). A deep learning-based multimodal biometric system using score fusion. IAES Int. J. Artif. Intell, 11(1), 65. Medjahed C. Rahmoun A. Charrier C. Mezzoudj F. ( 2022 ). A deep learning-based multimodal biometric system using score fusion . IAES Int. J. Artif. Intell , 11 ( 1 ), 65 . Search in Google Scholar

[26] Minaee, S., Abdolrashidi, A., Su, H., Bennamoun, M., & Zhang, D. (2023). Biometrics recognition using deep learning: A survey. Artificial Intelligence Review, 56(8), 8647-8695. Minaee S. Abdolrashidi A. Su H. Bennamoun M. Zhang D. ( 2023 ). Biometrics recognition using deep learning: A survey . Artificial Intelligence Review , 56 ( 8 ), 8647 - 8695 . Search in Google Scholar

[27] Yonghua Zhang, Haojie Wang & Zhenhua Pan. (2025). An efficient CNN accelerator for pattern-compressed sparse neural networks on FPGA. Neurocomputing128700-128700. Zhang Yonghua Wang Haojie Pan Zhenhua ( 2025 ). An efficient CNN accelerator for pattern-compressed sparse neural networks on FPGA . Neurocomputing 128700 - 128700 . Search in Google Scholar

[28] Dustin Kenefake, Rahul Kakodkar, Sahithi S. Akundi, Moustafa Ali & Efstratios N. Pistikopoulos. (2024). A multiparametric approach to accelerating ReLU neural network based model predictive control. Control Engineering Practice106041-106041. Kenefake Dustin Kakodkar Rahul Akundi Sahithi S. Ali Moustafa Pistikopoulos Efstratios N. ( 2024 ). A multiparametric approach to accelerating ReLU neural network based model predictive control . Control Engineering Practice 106041 - 106041 . Search in Google Scholar

[29] Qiang Zhang & Yuguang Fu. (2025). Effective traffic density recognition based on ResNet-SSD with feature fusion and attention mechanism in normal intersection scenes. Expert Systems With Applications125508-125508. Zhang Qiang Fu Yuguang ( 2025 ). Effective traffic density recognition based on ResNet-SSD with feature fusion and attention mechanism in normal intersection scenes . Expert Systems With Applications 125508 - 125508 . Search in Google Scholar