JOURNAL METRICS

CiteScore 2023: ℹCiteScore:

CiteScore is the number of citations received by a journal in one year to documents published in the three previous years, divided by the number of documents indexed in Scopus published in those same three years.

SCImago Journal Rank (SJR) 2023: ℹSCImago Journal Rank (SJR):

The SJR is a size-independent prestige indicator that ranks journals by their 'average prestige per article'. It is based on the idea that 'all citations are not created equal'. SJR is a measure of scientific influence of journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from It measures the scientific influence of the average article in a journal, it expresses how central to the global scientific discussion an average article of the journal is.

Source Normalized Impact per Paper (SNIP) 2023: ℹSource Normalized Impact per Paper(SNIP):

SNIP measures a source’s contextual citation impact by weighting citations based on the total number of citations in a subject field. It helps you make a direct comparison of sources in different subject fields. SNIP takes into account characteristics of the source's subject field, which is the set of documents citing that source.

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Most Read and Cited

An Extensive Review on Lung Cancer Detection Using Machine Learning Techniques: A Systematic Study

Eali Stephen Neal Joshua, Midhun Chakkravarthy, Debnath Bhattacharyya

https://doi.org/10.18280/ria.340314

Page 351-359

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Fresh and Rotten Fruits Classification Using CNN and Transfer Learning

Sai Sudha Sonali Palakodati, Venkata RamiReddy Chirra, Yakobu Dasari, Suneetha Bulla

https://doi.org/10.18280/ria.340512

Page 617-622

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Predictive Model for Network Intrusion Detection System Using Deep Learning

Venkatramaphanikumar Sstla, Venkata K.K. Kolli, Lakshmi K. Voggu, Ramyasri Bhavanam, Sasikala Vallabhasoyula

https://doi.org/10.18280/ria.340310

Page 323-330

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A Deep Learning Approach to Network Intrusion Detection Using Deep Autoencoder

Srikanthyadav Moraboena, Gayatri Ketepalli, Padmaja Ragam

https://doi.org/10.18280/ria.340410

Page 457-463

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A Deep Learning Method for Prediction of Cardiovascular Disease Using Convolutional Neural Network

Tulasi Krishna Sajja, Hemantha Kumar Kalluri

https://doi.org/10.18280/ria.340510

Page 601-606

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Prediction of Brain Stroke Severity Using Machine Learning

Vamsi Bandi, Debnath Bhattacharyya, Divya Midhunchakkravarthy

https://doi.org/10.18280/ria.340609

Page 753-761

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Deep CNN: A Machine Learning Approach for Driver Drowsiness Detection Based on Eye State

Venkata Rami Reddy Chirra, Srinivasulu ReddyUyyala, Venkata Krishna KishoreKolli

https://doi.org/10.18280/ria.330609

Page 461-466

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Avoiding Interoperability and Delay in Healthcare Monitoring System Using Block Chain Technology

Vejendla Lakshman Narayana, Arepalli Peda Gopi, Kosaraju Chaitanya

https://doi.org/10.18280/ria.330108

Page 45-48

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Violent Video Event Detection Based on Integrated LBP and GLCM Texture Features

B.H. Lohithashva, V.N. Manjunath Aradhya, D.S. Guru

https://doi.org/10.18280/ria.340208

Page 179-187

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Deep Convolution Features in Non-linear Embedding Space for Fundus Image Classification

Venkatesulu Dondeti, Jyostna Devi Bodapati, Shaik Nagur Shareef, Veeranjaneyulu Naralasetti

https://doi.org/10.18280/ria.340308

Page 307-313

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Efficient Wind Speed Forecasting Using Discrete Wavelet Transform and Artificial Neural Networks

Farid Berrezzek, Khaled Khelil, Tahar Bouadjila

https://doi.org/10.18280/ria.330607

Page 447-452

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An Efficient Method for Detection of Fake Accounts on the Instagram Platform

Saeid Sheikhi

https://doi.org/10.18280/ria.340407

Page 429-436

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A Machine Learning-Based Lightweight Intrusion Detection System for the Internet of Things

Samir Fenanir, Fouzi Semchedine, Abderrahmane Baadache

https://doi.org/10.18280/ria.330306

Page 203-211

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Security of Federated Learning: Attacks, Defensive Mechanisms, and Challenges

Mourad Benmalek, Mohamed Ali Benrekia, Yacine Challal

https://doi.org/10.18280/ria.360106

Page 49-59

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Lightweight Deep Learning for Malaria Parasite Detection Using Cell-Image of Blood Smear Images

Amin Alqudah, Ali Mohammad Alqudah, Shoroq Qazan

https://doi.org/10.18280/ria.340506

Page 571-576

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Developing IoT Based Smart Health Monitoring Systems: A Review

Ashikur Rahaman, Md. Milon Islam, Md. Rashedul Islam, Muhammad Sheikh Sadi, Sheikh Nooruddin

https://doi.org/10.18280/ria.330605

Page 435-440

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Attack and Anomaly Detection in IoT Networks Using Supervised Machine Learning Approaches

Himani Tyagi, Rajendra Kumar

https://doi.org/10.18280/ria.350102

Page 11-21

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Classification of White Blood Cells by Deep Learning Methods for Diagnosing Disease

Muhammed Yildirim, Ahmet Çinar

https://doi.org/10.18280/ria.330502

Page 335-340

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Staircase Detection to Guide Visually Impaired People: A Hybrid Approach

Ahsan Habib, Md. Milon Islam, Muhammad Nomani Kabir, Motasim Billah Mredul, Mahmudul Hasan

https://doi.org/10.18280/ria.330501

Page 327-334

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A Combined Approach of Sentimental Analysis Using Machine Learning Techniques

Ketan Gupta, Nasmin Jiwani, Neda Afreen

https://doi.org/10.18280/ria.370101

Page 1-6

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