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Debabrata Samanta

Researcher at Christ University

Publications -  90
Citations -  809

Debabrata Samanta is an academic researcher from Christ University. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 8, co-authored 52 publications receiving 251 citations.

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Journal ArticleDOI

Distributed Feedback Laser (DFB) for Signal Power Amplitude Level Improvement in Long Spectral Band

TL;DR: In this paper, a distributed feedback laser for signal power amplitude level improvement in the long spectral band of 1550-nm wavelength within supporting pumped wavelength of 1480-nm was presented, where the bias and modulation peak currents were varied to test the signal power level, peak signal amplitude variations after the fiber-optic channel and light detectors.
Journal ArticleDOI

An internet of health things‐driven deep learning framework for detection and classification of skin cancer using transfer learning

TL;DR: It has been observed that performance metric evaluation of proposed framework outperformed other pretrained architectures in term of precision, recall, and accuracy in detection and classification of skin cancer from skin lesion images.
Journal ArticleDOI

IoT-Based Smart Alert System for Drowsy Driver Detection

TL;DR: In this article, a smart alert technique for building intelligent vehicles that can automatically avoid drowsy driver impairment is presented. But drowsiness is a natural phenomenon in the human body that happens due to different factors, hence it is required to design a robust alert system to avoid the cause of the mishap.
Journal ArticleDOI

Malicious node detection using heterogeneous cluster based secure routing protocol (HCBS) in wireless adhoc sensor networks

TL;DR: The proposed heterogeneous cluster based secure routing scheme provides trust based secure network for detection of attacks such as wormhole and black hole caused by malicious nodes presence in wireless Adhoc network.
Proceedings ArticleDOI

An Overview: Security Issue in IoT Network

TL;DR: This study contains twelve different kinds of attacks, for example, low-graded attacks, average level attacks, great attacks ad particularly high intensity attacks along with their nature or behavior as well as resolutions to cater these attacks are discussed.