Shashank Mouli Satapathy

Orcid: 0000-0002-1665-8101

According to our database1, Shashank Mouli Satapathy authored at least 24 papers between 2013 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
A customizable framework for multimodal emotion recognition using ensemble of deep neural network models.
Multim. Syst., December, 2023

Automated Detection and Diagnosis of Skin-Lesion using Transfer Learning based YOLOv7 Approach.
Proceedings of the OITS International Conference on Information Technology, 2023

Application of Hybrid Approach towards Multi Aspect Classification and Analysis of Malware.
Proceedings of the OITS International Conference on Information Technology, 2023

2021
Community detection in dynamic networks: a comprehensive and comparative review using external and internal criteria.
Int. J. Syst. Assur. Eng. Manag., 2021

BFCNet: a CNN for diagnosis of ductal carcinoma in breast from cytology images.
Pattern Anal. Appl., 2021

Ontology-Based Modelling of IoT Design Patterns.
J. Inf. Knowl. Manag., 2021

A systematic review and bibliometric analysis of community detection methodologies in dynamic networks.
Int. J. Bus. Inf. Syst., 2021

Automated Diagnosis of Breast Cancer with RoI Detection Using YOLO and Heuristics.
Proceedings of the Distributed Computing and Internet Technology, 2021

Deep-Learning Approach with DeepXplore for Software Defect Severity Level Prediction.
Proceedings of the Computational Science and Its Applications - ICCSA 2021, 2021

Predicting Software Defect Severity Level using Sentence Embedding and Ensemble Learning.
Proceedings of the 47th Euromicro Conference on Software Engineering and Advanced Applications, 2021

2020
Mining patterns in open source software using software metrics and neural network models.
Int. J. Syst. Syst. Eng., 2020

2019
Method Level Refactoring Prediction on Five Open Source Java Projects using Machine Learning Techniques.
Proceedings of the 12th Innovations on Software Engineering Conference (formerly known as India Software Engineering Conference), 2019

2018
Application of SMOTE and LSSVM with Various Kernels for Predicting Refactoring at Method Level.
Proceedings of the Neural Information Processing - 25th International Conference, 2018

Applying Reverse Engineering Techniques to Analyze Design Patterns in Source Code.
Proceedings of the 2018 International Conference on Advances in Computing, 2018

2017
Empirical assessment of machine learning models for agile software development effort estimation using story points.
Innov. Syst. Softw. Eng., 2017

Empirical Assessment of Machine Learning Models for Effort Estimation of Web-based Applications.
Proceedings of the 10th Innovations in Software Engineering Conference, 2017

2016
Optimised class point approach for software effort estimation using adaptive neuro-fuzzy inference system model.
Int. J. Comput. Appl. Technol., 2016

Early stage software effort estimation using random forest technique based on use case points.
IET Softw., 2016

Effort estimation of web-based applications using machine learning techniques.
Proceedings of the 2016 International Conference on Advances in Computing, 2016

2014
Class point approach for software effort estimation using stochastic gradient boosting technique.
ACM SIGSOFT Softw. Eng. Notes, 2014

Use Case Point Approach Based Software Effort Estimation using Various Support Vector Regression Kernel Methods.
CoRR, 2014

Story Point Approach based Agile Software Effort Estimation using Various SVR Kernel Methods.
Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering, 2014

Class point approach for software effort estimation using various support vector regression kernel methods.
Proceedings of the 7th India Software Engineering Conference, Chennai, 2014

2013
Class point approach for software effort estimation using soft computing techniques.
Proceedings of the International Conference on Advances in Computing, 2013


  Loading...