Conference Papers

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    Semantic Segmentation for Autonomous Driving
    (Springer Science and Business Media Deutschland GmbH, 2023) Divakarla, U.; Bhat, R.; Madagaonkar, S.B.; Pranav, D.V.; Shyam, C.; Chandrashekar, K.
    Recently, autonomous vehicles (namely self-driving cars) are becoming increasingly common in developed urban areas. It is of utmost importance for real-time systems such as robots and automatic vehicles (AVs) to understand visual data, make inferences and predict events in the near future. The ability to perceive RGB values (and other visual data such as thermal, LiDAR), and segment each pixel into objects is called semantic segmentation. It is the first step toward any sort of automated machinery. Some existing models use deep learning methods for 3D object detection in RGB images but are not completely efficient when they are fused with thermal imagery as well. In this paper, we summarize many of these architectures starting from those that are applicable to general segmentation and then those that are specifically designed for autonomous vehicles. We also cover open challenges and questions for further research. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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    Implementing Service-Oriented Game-Theoretic Security Scheme for IoV Networks in Self-driving Cars
    (Springer Science and Business Media Deutschland GmbH, 2024) Divakarla, U.; Chandrasekaran, K.
    The security, privacy, and ethical issues surrounding the implementation of connected vehicles (CVs) are numerous. This paper provides a review of recent studies that investigate various IoT-related topics in self-driving cars, such as network architectures, security, and routing. It also suggests the implementation of Service-Oriented Game-Theoretic Security (SOS), which protects against phishing, DoS, and Sybil attacks. Here, we have combined our plan with Named the Networking (NDN), a method that focuses more on the substance and verifies the accuracy of the received data rather than examining the reliability of the sender. In order to accommodate our implementation and simulate the suggested method in a smaller-scale setting, we additionally change the current alert system model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.