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Journal Photo for ISCSITR-International Journal of Scientific Research in Artificial Intelligence and Machine Learning
Peer reviewed only Open Access

ISCSITR-International Journal of Scientific Research in Artificial Intelligence and Machine Learning (ISCSITR - IJSRAIML)

Publisher : International Society for Computer Science and Information Technology Research (ISCSITR)
Machine Learning Deep Learning Natural Language Processing (NLP)
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e-ISSN 3067-753X
p-ISSN 1668-1622X
Issue Frequency Half-Yearly
Est. Year 2020
Mobile 1234567809
DOI YES
Language English
APC YES
Impact Factor Assignee Google Scholar
Email editor@iscsitr.com, iscsitr@gmail.com

Journal Descriptions

International Journal of Scientific Research in Artificial Intelligence and Machine Learning (ISCSITR - IJSRAIML) is a peer-reviewed, open-access journal published by the International Society for Computer Science and Information Technology Research (ISCSITR). It serves as a platform for researchers, academics, and practitioners to publish high-quality research in artificial intelligence (AI) and machine learning (ML). The journal covers a wide range of topics, including deep learning, natural language processing, computer vision, robotics, and AI applications in various domains. IJSRAIML aims to foster innovation and knowledge dissemination in the AI and ML research community.

ISCSITR-International Journal of Scientific Research in Artificial Intelligence and Machine Learning (ISCSITR - IJSRAIML) is :-

  • International, Peer-Reviewed, Open Access, Refereed, Machine Learning, Deep Learning, Natural Language Processing (NLP), Speech Processing, Computer Vision, Image Processing, AI for Robotics, Autonomous Systems, AI in Healthcare, Biomedical Research, Cybersecurity, Threat Intelligence, Data Science, Big Data Analytics, IoT, Edge Computing, E-Learning , Online or Print , Half-Yearly Journal

  • UGC Approved, ISSN Approved: P-ISSN P-ISSN: 1668-1622X, E-ISSN: 3067-753X, Established: 2020,
  • Provides Crossref DOI

  • Not indexed in Scopus, WoS, DOAJ, PubMed, UGC CARE

Indexing

Publications of ISCSITR - IJSRAIML

Hierarchical Deep Learning Frameworks Enabling Dynamic Task Allocation and Real-Time Path Optimization in Mobile Robotic Fleets
Williiam Jones December, 2020
This study proposes a hierarchical deep learning framework designed to address dynamic task allocation and real-time path optimization in mobile robotic fleets operating in variable and reso...
Causal Inference in Neural Language Generation Models Through Interventional Probing and Counterfactual Evaluation
H R Anderson October, 2021
Understanding the causal mechanisms underlying neural language generation models (NLGM) is essential for improving model interpretability and controllability. This paper explores causal infe...
Self-Supervised Pretraining Strategies for Robust Transfer Learning under Domain and Distributional Shifts
James Richard November, 2022
Transfer learning has become a pivotal approach in modern machine learning pipelines, particularly when labeled data is limited. However, its robustness under domain and distributional shift...
Impact of Federated Learning Techniques on Data Privacy and Model Performance in Distributed Artificial Intelligence Networks
Riya Singh January, 2024
Federated learning (FL) has emerged as a transformative paradigm in distributed artificial intelligence (AI) that emphasizes decentralized model training while preserving data privacy. This ...
Dynamic Optimization of Network Resilience in Cloud Environments Using Artificial Intelligence Algorithms
Melanie D. January, 2024
Cloud environments require robust and adaptive networks to ensure service continuity in the face of evolving threats and challenges. This paper investigates the dynamic optimization of netwo...
AI-Augmented Graph Databases for Judicial Case Management: A Scalable AWS-Powered Framework for Relationship Analysis and Decision Support
Raja Mohan April, 2025
The objective of this study is to modernise court case management through an AI aided graph database that operates in AWS technologies. Amazon Neptune organises intricate legal connections,...
Advanced Algorithmic Approaches to Data-Driven Optimization for Improving Strategic Decision-Making in Marketing Analytics
JAMES ANTO March, 2025
In recent years, the application of advanced algorithmic approaches to data-driven optimization has garnered significant attention in the field of marketing analytics. This paper explores ho...
An Integrated Framework for Optimizing Case Management Systems through Context-Aware Artificial Intelligence and Dynamic Workflow Reengineering
Leticia Thais January, 2024
Case management systems (CMS) are fundamental in industries like healthcare, law, and customer service, yet they often suffer from rigidity, inefficiency, and poor adaptability. This paper p...
Impact of Federated Learning Techniques on Data Privacy and Model Performance in Distributed Artificial Intelligence Networks
Riya Singh January, 2024
Federated learning (FL) has emerged as a transformative paradigm in distributed artificial intelligence (AI) that emphasizes decentralized model training while preserving data priva...
Temporal Modeling of Longitudinal Patient Trajectories Using Recurrent Neural Architectures for Prognostic Risk Stratification in Multicenter Clinical...
Research Scholar October, 2023
Prognostic risk stratification is crucial for optimizing care delivery in clinical settings. This paper investigates the application of recurrent neural network (RNN) architectures, such as ...