Prashant Kumar
Central Electronics Engineering Research Institute
8 Papers
3 Citations
Prashant Kumar is an academic researcher from Central Electronics Engineering Research Institute. The author has contributed to research in topics: Computer science & Object detection. The author has an hindex of 2, co-authored 8 publications. Previous affiliations of Prashant Kumar include Academy of Scientific and Innovative Research.
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Papers
Real-Time Concrete Damage Detection Using Deep Learning for High Rise Structures
TL;DR: In this paper, a real-time multi-drone damage detection system using one of the advance deep learning models called You Look Only Once-version3 (YOLO-v3) for high-rise civil structures was proposed.
Automatic Multiclass Instance Segmentation of Concrete Damage Using Deep Learning Model
TL;DR: In this article, Mask Region-Based Convolutional Neural Network (Mask R-CNN) was used to detect and segment defects in civil infrastructure with multiple objects, such as Horizontal Crack, Vertical Crack, Diagonal Crack, Branch Crack, and Spall.
Spin dynamics investigations of multifunctional ambient scalable Fe3O4 surface decorated ZnO magnetic nanocomposite using FMR.
Saurabh Pathak,Saurabh Pathak,Saurabh Pathak,Rajni Verma,Sakshi Singhal,Raghav Chaturvedi,Prashant Kumar,Pragati Sharma,R. P. Pant,Xu Wang +9 more
TL;DR: In this article, the authors investigated the magnetic properties of ZnO nanocomposites using ferromagnetic resonance (FMR) and found that the magnetic ordering, exchange coupling and anisotropy of the FZNC has been investigated.
Intelligent Home with Air Quality Monitoring
TL;DR: An intelligent home with air quality monitoring (AQM) system that brings controlling and monitoring of devices and appliances, and monitoringof home environment together in real time is proposed.
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Real-Time, YOLO-Based Intelligent Surveillance and Monitoring System Using Jetson TX2
Prashant Kumar,Prashant Kumar,S. Narasimha Swamy,S. Narasimha Swamy,Pramod Kumar,Pramod Kumar,Gaurav Purohit,Gaurav Purohit,Kota Solomon Raju,Kota Solomon Raju +9 more
- 01 Jan 2021
TL;DR: In this paper, a real-time object detection and alert system (ODAS) is proposed, which uses the YOLO framework to detect objects within images and live videos.
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