S. Raghavendra

22 papers Journal 18Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A Hybrid Deep Learning Approach With Explainable AI for Diabetic Retinopathy Classification. IEEE Access Gogulamudi Pradeep Reddy, Preethi Deepak Javali, Ramyashree, S. Raghavendra, C. B. Chandrakala, P. S. Venugopala
2026	J	`jnl`	AURA-Net: A Deep Learning Framework for Robust Authorship Verification in Print-and-Capture Resistant Image Watermarking. IEEE Access Ramyashree, P. Shashwath, M. S. Muneshwara, S. Raghavendra, B. N. Anoop, P. S. Venugopala
2026	J	`jnl`	Domain-Adaptive Panoramic Video Generation Using Image Diffusers. IEEE Access P. Anujna Prabhu, S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, P. V. Arun Kumar, N. D. Adesh, C. B. Chandrakala
2026	J	`jnl`	EMAF-Net: An Edge-Aware Super-Resolution Framework for Enhanced Object Detection and Semantic Annotation. IEEE Access Ramyashree, Sanath Prabhu, S. Raghavendra, B. N. Anoop
2025	J	`jnl`	ESRVA: Enhanced Super-Resolution and Visual Annotation Model for Object-Level Image Interpretation Using Deep Learning. IEEE Access Ramyashree, Ashmika, S. Raghavendra, B. N. Anoop, P. S. Venugopala
2025	J	`jnl`	ETIA: Enhancing Text2Image Surround View Scene Generation With Semantic Annotation via Diffusion for Autonomous Driving. IEEE Access Ramyashree, S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, P. V. Arun Kumar, P. Malashree
2025	J	`jnl`	Efficient Anchor-Free Unified Framework for Panoptic Part Segmentation in Real-Time and Resource-Constrained Environments. IEEE Access S. Raghavendra, Shambhavi Jha, S. K. Abhilash, Venu Madhav Nookala, Ramyashree, B. N. Anoop
2025	J	`jnl`	Joint Camera-LiDAR Scene Synthesis and Perception for Autonomous Driving. IEEE Access S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, P. V. Arun Kumar, B. N. Anoop, Ramyashree
2025	J	`jnl`	Resilient Multimedia Embedding in DICOM Images: A Robustness Evaluation Under Multiple Attacks. IEEE Access Ramyashree, P. S. Venugopala, S. Raghavendra, Vijay S. Kubihal, B. Ashwini
2025	J	`jnl`	SVPDSA: Selective View Perception Data Synthesis With Annotations Using Lightweight Diffusion Network. IEEE Access S. Raghavendra, Vijayalakshmi, Vainidhi, S. K. Abhilash, Venu Madhav Nookala, P. V. Arun Kumar, Ramyashree
2025	J	`jnl`	YLOMF: You Look Once for Multi-Feature - A Multi-Feature Multi-Task Network for Intelligent Real-Time Perception in Autonomous Driving. IEEE Access B. N. Anoop, S. K. Abhilash, Venu Madhav Nookala, S. Prita, S. Raghavendra
2023	J	`jnl`	DLMNN Based Heart Disease Prediction with PD-SS Optimization Algorithm. Intell. Autom. Soft Comput. S. Raghavendra, Vasudev Parvati, R. Manjula, Ashok Kumar Nanda, Ruby Singh, D. Lakshmi, S. Velmurugan
2022	—	`conf`	Analysis and Prognosis of Water Quality for River Ganga Using Water Quality Index. ATIS Yash Bijalwan, Pranav Chaudhari, Om Sharma, S. Raghavendra
2022	J	`jnl`	Artificial humming bird with data science enabled stability prediction model for smart grids. Sustain. Comput. Informatics Syst. S. Raghavendra, S. Neelakandan, Prakash Mohan, B. T. Geetha, S. Mary Rexcy Asha, Michaelraj Kingston Roberts
2022	—	`conf`	Comparative Study of Sentiment Analysis on Cyber Security Related Multi-sourced Data in Social Media Platforms. ATIS Keshav Kapur, Rajitha Harikrishnan, S. Raghavendra
2022	J	`jnl`	Multilayer Stacked Probabilistic Belief Network-Based Brain Tumor Segmentation and Classification. Int. J. Found. Comput. Sci. S. Raghavendra, Awari Harshavardhan, S. Neelakandan, R. Partheepan, Ranjan Walia, V. Chandra Shekhar Rao
2020	J	`jnl`	Hybrid energy-efficient and QoS-aware algorithm for intelligent transportation system in IoT. Int. J. Grid Util. Comput. Srinidhi NN, G. P. Sunitha, S. Raghavendra, S. M. Dilip Kumar, Victor Chang
2017	J	`jnl`	An Analysis of Leg Muscle Stretch Using 3D Digital Image Correlation. Int. J. Organ. Collect. Intell. G. B. Praveen, S. Raghavendra, Victor I. C. Chang
2016	J	`jnl`	Hybrid data mining model for the classification and prediction of medical datasets. Int. J. Knowl. Eng. Soft Data Paradigms S. Raghavendra, M. Indiramma
2015	J	`jnl`	Multiple ligand simultaneous docking (MLSD): A novel approach to study the effect of inhibitors on substrate binding to PPO. Comput. Biol. Chem. S. Raghavendra, S. J. Aditya Rao, Vadlapudi Kumar, C. K. Ramesh
2005	—	`conf`	Asynchronous multimedia annotations for web-based collaboration in biology education. Storage and Retrieval Methods and Applications for Multimedia Dragutin Petkovic, E. Lank, F. A. Ramirez, S. Raghavendra, F. Chen, C. Pekiner, A. Fregoso, A. Marquez
2004	—	`conf`	BioMedia: multimedia information systems for biology research, education, and collaboration. Storage and Retrieval Methods and Applications for Multimedia E. Lank, Dragutin Petkovic, F. A. Ramirez-Weber, J. Hafernik, J. Hsieh, J. Maag, S. Pathuri, C. Pekiner, S. Raghavendra

Nicolò Altamura is a security engineer and computer science researcher specializing in software protection, reverse engineering, program analysis, and binary deobfuscation. He holds a master's degree in Computer Science and Engineering from the University of Verona, graduating with honors, and works at emproof, focusing on software protection and the challenges of analyzing and understanding compiled software.

His research explores the relationship between program analysis and code obfuscation, with particular emphasis on how software transformations affect the ability of automated tools to recover program behavior. His interests span static analysis, binary analysis, decompilation, reverse engineering, and techniques for analyzing and simplifying obfuscated code.

Beyond academic research, Nicolò develops and contributes to tools for reverse engineering and software analysis. His projects include obfuscation_analysis, a Binary Ninja plugin for analyzing and simplifying obfuscated code; Pocket, an obfuscator for mixed Boolean-arithmetic expressions; and ptxNinja, a tool for reverse engineering NVIDIA GPU code represented in the PTX virtual instruction set.

His research also extends to binary datasets and software evolution. In 2026, he co-authored ASSEMBLAGE-DEEPHISTORY: A Cross-Build Binary Dataset with Temporal Coverage, a research work addressing the availability of binary data across multiple software builds and points in time, supporting research into binary analysis and changes between program versions.

Across his research, engineering work, and open-source contributions, Nicolò focuses on advancing the understanding, analysis, and protection of software against increasingly sophisticated obfuscation and reverse-engineering challenges.

Nicolò Altamura is not a football player. Please avoid reporting this kind of infromation.