Sujatha
@mrcet.ac.in
Head of The Department-CSE(AIML)
Malla Reddy College of Engineering and Technology
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Engineering, Computer Science, Artificial Intelligence
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Mundlamuri Venkata Rao, Divya Midhunchakkaravarthy, and Sujatha Dandu
Springer Nature Singapore
Mundlamuri Venkata Rao, Divya Midhunchakkaravarthy, and Sujatha Dandu
Springer Science and Business Media LLC
Mundlamuri Venkata Rao, Divya Midhunchakkaravarthy, and Sujatha Dandu
Springer Science and Business Media LLC
Mandapati Siva Sai Krishna Varma, S Abhishek, Sujatha Dandu, and Anjali T
IEEE
The method of recognizing and finding a human by their face in an image is called Human Face Detection and Recognition (HFDR). Application of Biometric method in detecting a human's Identity is called as HFD system. HFDR is a verification system designed to determine one's identity. Innovation in science and technology is rapidly achieving the peak level day by day. Artificial Intelligence (AI) and Machine Learning (ML) are the two such innovative inventions that kicked it up a notch and have turned the world to the next phase. This research is intended to detect and recognize faces using HFDR using ML. The consequences of the simulation experiment clearly show that the HFDR using ML method is best known for its accuracy in HFDR compared to the other algorithms used for Human Face Detection (HFD). The exactness of the proposed HFDR using ML method is illustrated through the experimental outcomes.
Mundlamuri Venkata Rao, Divya Midhunchakkaravarthy, and Sujatha Dandu
World Scientific Pub Co Pte Ltd
A worm is a standalone program, which is self-replicating malware that distributes itself to other computers and networks. An Internet worm can spread across the network and infect millions of computers in truly little time and the damages caused from such attacks are considered extremely high. In addition, these worms also affect the network packet and its performance, where the packets are analyzed by the signature-based intrusion detection system (IDS) and the network performance is analyzed by the NetFlow based IDS. Hence, this article proposes a joint detection of both the signature based and NetFlow based Internet worms using deep learning convolution neural network (DLCNN) with respect to various attacks and it can also prevent the suspicious actions of attackers (cyber-criminals). Additionally, it provides the security for users’ data maintenance, countermeasures, and controls the spreading of the internet worms. The effectiveness of proposed DLCNN model is evaluated using both packet capture (PCAP) and KDD-CUP-99 datasets. Finally, various quality metrics are employed to disclose the superiority of proposed DLCNN model as compared existing machine learning, and back propagated neural network models.
S. Shanthi, D. Sujatha, V. Chandrasekar, and S. Nagendra Prabhu
Springer Singapore
Thayyaba Khatoon, A Govardhan, and D Sujatha
IEEE
Research in Biomedicine is increasing rapidly day by day and the need for maintaining the biomedical literature is also a tedious task. Data Curators, Doctors, Scientific Researchers have a requirement of analyzing biomedical articles for Scientific discoveries and scholarly knowledge from this vast collection of data to take a proper prediction. Biomedical data includes a collection of genes and protein related information and the mutations of the above which leads to diseases. This kind of hidden knowledge and relationships between above mentioned entities can be mined with proper preprocessing methods. This paper illustrates the comparison of various preprocessing methods used on biomedical data and the best combination of methods can be used for the retrieval of hidden intrinsic knowledge and patterns from Biomedical Literature Data Sources.
Chaitanya Muppala, Sujatha Dandu, and Anusha Potluri
Springer Singapore
A. M. Viswa Bharathy, V. Chandrasekar, and D. Sujatha
Springer Singapore
Venkateswara Reddy Eluri, Ch. Ramesh, Siva Naga Dhipti, and D. Sujatha
Springer Singapore
S. Shanthi, Padmalaya Nayak, and Sujatha Dandu
Springer Singapore
Sujatha Dandu and B. L. Deekshatulu
Springer International Publishing