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
Anam-Net: Anamorphic Depth Embedding-Based Lightweight CNN for Segmentation of Anomalies in COVID-19 Chest CT Images
Naveen Paluru,Aveen Dayal,Havard Bjorke Jenssen,Tomas Sakinis,Linga Reddy Cenkeramaddi,Jaya Prakash,Phaneendra K. Yalavarthy +6 more
TL;DR: Paluru et al. as discussed by the authors proposed anamorphic depth embedding-based lightweight CNN, called Anam-Net, to segment anomalies in COVID-19 chest CT images, which has 7.8 times fewer parameters compared to the state-of-the-art UNet (or its variants), making it lightweight capable of providing inferences in mobile or resource constraint (point of care) platforms.
Journal ArticleDOI
GPS Spoofing Detection and Mitigation for Drones Using Distributed Radar Tracking and Fusion
TL;DR: The spoofing scenario results show that using the predicted fusion state provides the same accuracy as a GPS receiver in a clean environment, and because the innovation is calculatedUsing the predicted fused state, there is no effect on the number of satellite signals on PRMSE.
Journal ArticleDOI
Mini-COVIDNet: Efficient Lightweight Deep Neural Network for Ultrasound Based Point-of-Care Detection of COVID-19
TL;DR: In this paper, the authors developed a lightweight mobile friendly efficient deep learning model for detection of COVID-19 using lung US images, which can achieve the highest accuracy of 83.2% and requires a training time of only 24 min.
Journal ArticleDOI
Localization and Activity Classification of Unmanned Aerial Vehicle Using mmWave FMCW Radars
Prabhat Kumar Rai,Henning Idsoe,Rajesh Reddy Yakkati,Abhinav Kumar,Mohammed Zafar Ali Khan,Phaneendra K. Yalavarthy,Linga Reddy Cenkeramaddi +6 more
TL;DR: A novel localization and activity classification method for aerial vehicle using mmWave frequency modulated continuous wave (FMCW) Radar enables the utilization of mmWave Radars in security surveillance and privacy monitoring applications.
Proceedings ArticleDOI
Self-Powered IoT Device for Indoor Applications
Rolf Arne Kjellby,Thor Eirik Johnsrud,Svein Erik Loetveit,Linga Reddy Cenkeramaddi,Mohamed Hamid,Baltasar Beferull-Lozano +5 more
TL;DR: This paper presents a proof of concept for selfpowered Internet of Things (IoT) device, which is maintenance free and completely self-sustainable through energy harvesting, which can potentially last for more than 5 months on the coin cell battery without any energy harvesting.