Anurag Goswami
Orcid: 0000-0001-5569-2292
According to our database1,
Anurag Goswami
authored at least 24 papers
between 2013 and 2024.
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Bibliography
2024
FakeIDCA: Fake news detection with incremental deep learning based concept drift adaption.
Multim. Tools Appl., March, 2024
2023
Adaptive windowing based recurrent neural network for drift adaption in non-stationary environment.
J. Ambient Intell. Humaniz. Comput., October, 2023
Deep learning-based important weights-only transfer learning approach for COVID-19 CT-scan classification.
Appl. Intell., March, 2023
HSDH: Detection of Hate Speech on social media with an effective deep neural network for code-mixed Hinglish data.
Proceedings of the 14th International Conference on Computing Communication and Networking Technologies, 2023
2022
AENeT: an attention-enabled neural architecture for fake news detection using contextual features.
Neural Comput. Appl., 2022
Neural Comput. Appl., 2022
Future Gener. Comput. Syst., 2022
2021
DeepFakE: improving fake news detection using tensor decomposition-based deep neural network.
J. Supercomput., 2021
EchoFakeD: improving fake news detection in social media with an efficient deep neural network.
Neural Comput. Appl., 2021
FakeBERT: Fake news detection in social media with a BERT-based deep learning approach.
Multim. Tools Appl., 2021
A transfer learning with structured filter pruning approach for improved breast cancer classification on point-of-care devices.
Comput. Biol. Medicine, 2021
A Heuristic-Driven and Cost Effective Majority/ Minority Logic Synthesis for Post-CMOS Emerging Technology.
IEEE Access, 2021
Proceedings of the 13th International Conference on Agents and Artificial Intelligence, 2021
MCNNet: Generalizing Fake News Detection with a Multichannel Convolutional Neural Network using a Novel COVID-19 Dataset.
Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021
2020
Cogn. Syst. Res., 2020
Artif. Intell. Rev., 2020
2018
Proceedings of the 2018 IEEE International Symposium on Software Reliability Engineering Workshops, 2018
Validating Requirements Reviews by Introducing Fault-Type Level Granularity: A Machine Learning Approach.
Proceedings of the 11th Innovations in Software Engineering Conference, ISEC 2018, Hyderabad, India, February 09, 2018
2016
Proceedings of the 2016 IEEE International Symposium on Software Reliability Engineering Workshops, 2016
Using Eye Tracking to Investigate Reading Patterns and Learning Styles of Software Requirement Inspectors to Enhance Inspection Team Outcome.
Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement, 2016
2015
Using Learning Styles of Software Professionals to Improve Their Inspection Team Performance.
Int. J. Softw. Eng. Knowl. Eng., 2015
2014
Improving the Cost Effectiveness of Software Inspection Teams: An Empirical Investigation.
Proceedings of the 26th International Conference on Software Engineering and Knowledge Engineering, 2014
2013
An empirical study of the effect of learning styles on the faults found during the software requirements inspection.
Proceedings of the IEEE 24th International Symposium on Software Reliability Engineering, 2013