Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Partha Pratim Sarangi"'
Publikováno v:
2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c9fb2e77b588666d45ff2ea642de58af
https://doi.org/10.1109/icccmla56841.2022.9989104
https://doi.org/10.1109/icccmla56841.2022.9989104
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing. 13:1867-1898
Ear based identity recognition subject to uncontrolled conditions such as illumination changes, pose variation, low contrast, partial occlusion and noise, is an active research area in the field of biometrics. Meanwhile, multimodal biometrics is beco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3522760c47cfdf0930c5cca3624939db
https://doi.org/10.1007/s12652-021-02952-0
https://doi.org/10.1007/s12652-021-02952-0
Publikováno v:
Evolutionary Intelligence. 13:443-461
Recently, the ear biometric has received much attention for human recognition due to its unique shape and rich local features. However, extracting discriminative features from ear images is a crucial task in presence of illumination changes, low cont
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::99571a9f6c61921efcde93cffd6a72aa
https://doi.org/10.1007/s12065-019-00311-9
https://doi.org/10.1007/s12065-019-00311-9
Autor:
Partha Pratim Sarangi, Madhumita Panda
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9789813367807
In this paper, we propose an improved multimodal ear and profile face biometrics for human identity recognition under uncontrolled conditions such as illumination changes, pose variation, low contrast, partial occlusion, and blur. In this framework,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d14cc804a660e1956782cdca1465815e
https://doi.org/10.1007/978-981-33-6781-4_2
https://doi.org/10.1007/978-981-33-6781-4_2
Autor:
Rai, Pradeep, Usman, Mohammed, Paras Jain, Shukla, Man Mohan, Chaurasia, Ruchi, Anurag Tewari, Shukla, Nidhi, Srivastava, Atul, Mohd Yasir Arafat, Partha Pratim Sarangi, Piyush Bhushan Singh, Abhishek Srivastava, Raisul Hasan, Sonam Srivastava, Kumari, Richa, Krati Gupta, Gupta, Ruchi, Bhola Chaurasia, Dwivedi, Arun KUMAR, Ankush Verma, Dr. Dileep Kumar Yadav, Satyasundara Mahapatra, Ved Prakash Bhardwaj, Ajar Nath Yadav, Rachit Patel, Xiangyang Hu, Kishtwal, Ashok, Vishal Kamble, Shadab, Azhar, Faujdar, Neetu, Shah, Mohammad Imran, Sahni, Dinesh, Purnima Bhandari, Singh, Suren, Starcic, Andreja Istenic, Gaurav KUMAR Upadhyay, Jeong, Young-Sik, Driscoll, Nicola O, Dugyala, Raman, Hyderabad Shrawan Kumar, Rajanikanth Aluvalu, K Mallikharjuna Babu, Akhil, Jabbar, Muni Sekhar, Mallellu Sai Prashanth, Hyderabad C Prof, S K Prashanth, Kulkarni, Vivek, Vipin Tyagi, Kumar, Ashwani, Gundabathula Venkateswara Rao, Dheerendra Singh Gangwar, P K Gupta
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aa2277aecd4f89c3a436bef79f7e408c
Publikováno v:
Multimedia Tools and Applications. 78:9595-9623
Achieving higher recognition performance in uncontrolled scenarios is a key issue for ear biometric systems. It is almost difficult to generate all discriminative features by using a single feature extraction method. This paper presents an efficient
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2d65f21d732a583296be87fe22cc1cef
https://doi.org/10.1007/s11042-018-6489-0
https://doi.org/10.1007/s11042-018-6489-0
Autor:
Partha Pratim Sarangi, Madhumita Panda, Subhashree Mishra, Bhabani Shankar Prasad Mishra, Banshidhar Majhi
Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can
Publikováno v:
RAIT
In recent years, many researchers have shown interest in combining features of different biometrie traits to improve recognition performance of the biometrie systems. In this paper, we examine the feature-level fusion of two contactless biometric mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::426f714592a29545c7379b8672344398
https://doi.org/10.1109/rait.2018.8389035
https://doi.org/10.1109/rait.2018.8389035