Papers by HAREESH S
IJCRT, 2024
This review paper offers a comprehensive examination of recent advancements in the field of bone ... more This review paper offers a comprehensive examination of recent advancements in the field of bone fracture detection using deep learning methods. As the demand for accurate and efficient fracture diagnosis continues to grow, the paper systematically explores state-of-the-art deep learning algorithms, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and hybrid models. The survey also investigates their application across various imaging modalities, including X-rays, CT scans, and MRIs. Furthermore, the paper evaluates the strengths, limitations, and performance metrics of these approaches, while also identifying emerging trends, challenges, and future research directions. This review aims to guide researchers and healthcare professionals in the development of robust and reliable tools for bone fracture detection.
International Journal of Trend in Research and Development, 2024
This survey paper provides a comprehensive overview of recent advancements in bone fracture detec... more This survey paper provides a comprehensive overview of recent advancements in bone fracture detection and classification methodologies, leveraging cutting-edge technologies in medical imaging and artificial intelligence. As the demand for accurate and efficient fracture diagnosis continues to grow, this paper systematically reviews and analyzes state-of-the-art techniques, including deep learning algorithms, computer-aided diagnosis systems, and innovative image processing methods. The survey explores the strengths and limitations of various approaches, highlighting their applicability across different imaging modalities such as X-rays, CT scans, and MRIs. Additionally, the paper discusses emerging trends, challenges, and potential future directions in the field, aiming to guide researchers, healthcare professionals, and technologists toward the development of more robust and reliable tools for bone fracture detection and classification.
Conference Presentations by HAREESH S
Dept of Computer Science, St. Joseph's College, Trichy, 2024
Quantum-safe deep learning is an emerging field that aims to develop techniques for training and ... more Quantum-safe deep learning is an emerging field that aims to develop techniques for training and deploying deep learning models that are resistant to quantum attacks. As quantum computing power continues to increase, it becomes increasingly important to ensure that our current encryption methods and security protocols will remain effective. This survey provides an overview of the current state of quantum-safe deep learning, including the challenges and opportunities in this field, as well as the existing and proposed solutions. We also discuss the potential impact of quantum-safe deep learning on futureproofing cloud security.
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Papers by HAREESH S
Conference Presentations by HAREESH S