L
Linga Reddy Cenkeramaddi
Researcher at University of Agder
Publications - 111
Citations - 753
Linga Reddy Cenkeramaddi is an academic researcher from University of Agder. The author has contributed to research in topics: Computer science & Radar. The author has an hindex of 8, co-authored 61 publications receiving 214 citations. Previous affiliations of Linga Reddy Cenkeramaddi include Norwegian University of Science and Technology & University of Bergen.
Papers
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Journal ArticleDOI
Recent Advances and Future Directions of Microwave Photonic Radars: A Review
Saran Srihari Sripada Panda,Trilochan Panigrahi,Saidi Reddy Parne,Samrat L. Sabat,Linga Reddy Cenkeramaddi +4 more
TL;DR: This review article overviews the different components of microwave photonic radar, different design challenges, and issues pertaining to it, and presents a comparative study of different MWP radars on different applications.
Proceedings ArticleDOI
Multi-application Based Network-on-Chip Design for Mesh-of-Tree Topology Using Global Mapping and Reconfigurable Architecture
TL;DR: This paper outlines a multi-application mapping for Mesh-of-Tree (MoT) topology based Network-on-Chip (NoC) design using reconfigurable architecture and shows significant improvement in terms of communication cost after reconfiguration.
Proceedings ArticleDOI
Design and Prototype Implementation of Long-Range Self-Powered Wireless IoT Devices
RolfArne Kjellby,Linga Reddy Cenkeramaddi,Thor Eirik Johnsrud,Geir Jevne,Svein Erik Lotveit,Baltasar Beferull Lozano,Soumya Joshi +6 more
TL;DR: This paper presents the design and prototype implementation of long-range self-powered wireless IoT devices using nRF52840 based on energy harvesting in both star and multi-hop configurations with optimized custom protocols.
Journal ArticleDOI
Classification of Targets Using Statistical Features from Range FFT of mmWave FMCW Radars
Jyoti Bhatia,Aveen Dayal,Ajit Jha,Santosh Kumar Vishvakarma,Joshi Soumya,M. B. Srinivas,Phaneendra K. Yalavarthy,Abhinav Kumar,V. Lalitha,Sagar Koorapati,Linga Reddy Cenkeramaddi +10 more
TL;DR: The presented classification technique extends the potential of mmWave FMCW radar beyond the detection of range, velocity, and AoA to classification, and will be more robust in computer vision, visual perception, and fully autonomous ground control and traffic management cyber-physical systems.
Journal ArticleDOI
Video Hand Gestures Recognition Using Depth Camera and Lightweight CNN
David González León,Jade Gröli,Sreenivasa Reddy Yeduri,Daniel Rossier,Romuald Mosqueron,Om Jee Pandey,Linga Reddy Cenkeramaddi +6 more
TL;DR: This work presents the video based hand gestures recognition using the depth camera and a light weight convolutional neural network (CNN) model, and compares the accuracy of the proposed light weight CNN model with the state-of-the hand gesture classification models.