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Ashok Kumar Sahoo

Associate Professor
Computer Science & Engineering
Sharda University
India

Biography

Ashok Kumar Sahoo completed his PhD in Computer Science & Engineering from Sharda University. His topic of research was "Computer Recognition of Indian Sign Language". His publications include more than fifteen papers in International Refereed Journals, presented three papers in International conferences. His research interests include Pattern Recognition, Machine Learning, Neural Networks and Intelligent systems. He has more than 18 years of teaching experience in various technical Institutions. His teaching interests include Design and Analysis of Algorithms, Data Structures, Computer Networks, Programming Paradigms, Pattern Recognition and C/C++/Java Programming. He has been working in this University since November 2003. He is currently working as an Associate Professor in Computer Science & Engineering Department. He is also actively involved in various research and administrative activities of the University.

Research Interest

Algorithms Artificial Intelligence Data Structures Soft Computing Computer Networks Pattern Recognition  

Publications

  • Ashok Kumar Sahoo and Gouri Sankar Mishra, "Computer Recognition of Isolated Numeral Signs of Indian Sign Language", International Conference on the occasion of Silver Jubilee of the Indian Society of Industrial & Applied Mathematics (ISIAM) at Sharda University, Greater Noida, 29-31, January, 2016.

  • Mir Aman Sheheryar, Pradeep Kumar Mishra and Ashok Kumar Sahoo, " A review on CAPTCHA generation and evaluation techniques", ARPN Journal of Engineering and Applied Sciences. vol. 11, no. 9, 2016, pp: 5800-5811. (Indexed in Scopus, SJR quartile = Q4, SJR value = 0.157) [ISSN 1819-6608]

  • Gouri Sankar Mishra, Ashok Kumar Sahoo and Kiran Kumar Ravulakollu, “Word based statistical machine translation from English text to Indian Sign Language”, Journal of Engineering and Applied Sciences. vol. 12, no. 2, 2017, pp: 481-488. (Indexed in Scopus, SJR quartile = Q4, SJR value = 0.157) [ISSN 1819-6608]

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