V. Thamilarasi
@srisaradacollege.ac.in
ASSISTANT PROFESSOR IN COMPUTER SCIENCE
SRI SARADA COLLEGE FOR WOMEN(AUTONOMOUS)
ASSISTANT PROFESSOR IN SRI SARADA COLLEGE FOR WOMEN(AUTONOMOUS)
EDUCATION
M.Sc, M.Phil, MCA., Ph.D IN COMPUTER SCIENCE
RESEARCH INTERESTS
MEDICAL IMAGE PROCESSING, DATA MINING
FUTURE PROJECTS
Efficient Classification by RESNET-50 and compare by deep learning architectures for lung chest X-ray images
I have already completed this work and i need collaboration for SCI publishing only
Applications Invited
Interested persons communicate me
Scopus Publications
Scopus Publications
V. Thamilarasi, Pramod Kumar Naik, Isha Sharma, V. Porkodi, M. Sivaram, and M. Lawanyashri
IEEE
This abstract discusses the transformational capacity of Shor’s Algorithm and quantum cryptography in quantum computing. However, Shor’s Algorithm poses a problem to classical cryptographic systems such as RSA encryption because of its apparent capacity to multiply speed the integer factorization. This approach relies on multimillions qubit quantum computers with systematic error correction which have yet to be implemented. Quantum cryptography revolutionizes secure communication via Quantum Key Distribution (QKD). It uses quantum mechanics to design the unbreakable key exchange system that can identify eavesdropping. Despite the prospect, quantum cryptography is hampered by limits in distances and speeds of QKD transmission. Quantum repeaters and satellite-based QKD make it possible to overcome these difficulties and facilitate the creation of a secure global communication grid. The comparison of classical and quantum cryptography illustrates an evolution from complexity-based security to quantum physics security, which is immune to quantum computational attacks. Reports of quantum supremacy and QKD network development are stages on the way towards quantum computers and cryptography. Technology challenges on this approach include scalability of quantum systems, qubit coherence, and error correction. Quantum computing has the potential to transform computer and communication security. This route involves innovation in quantum technology development, as well as integration issues. Quantum computing and cryptography’s full potential would lead to an age of new computational possibilities that will change the encryption of data and secure communication.
A. Asaithambi and V. Thamilarasi
IEEE
This paper investigates the application of several deep learning architectures such as VGG-16, VGG-19, ResNet-50, and Xception Net for lung chest X-ray images, with 5, 10, and 15 epochs, and different optimizers such as Adam, SGD, and RMSProp, and a learning rate of 0.0001. The investigation finds that when adaptive gradient is used, the VCG-16 architecture achieves 68% accuracy; VCG-19 achieves 67% accuracy; ResNet-50 achieves 98.67% accuracy; and the Xception Net architecture achieves less than 50% accuracy. With further experimentation using 5, 10, and 15 epochs and optimizers such as Adam, SGD, and RMSProp, a 100% accuracy was achieved with 15 epochs for the VGG-16, VGG-19, and ResNet-50 architectures. However, Xception Net has been able to achieve only 70% accuracy with these optimizers.