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Advances in Machine Learning & Artificial Intelligence(AMLAI)

ISSN: 2769-545X | DOI: 10.33140/AMLAI

Impact Factor: 1.3*

Aims and Scope

Journal DOI: 10.33140/AMLAI

Advances in Machine Learning & Artificial Intelligence (ISSN: 2769-545X) is a peer-reviewed open-access journal focused on basic science and clinical aspects of Robotics, Artificial Intelligence, and Mechatronics in the last 3 yrs. The quality of the Editorial Board follows the Peer review process. The time to publish the articles from the date of submission is a maximum of 30-35 days.

The scope of the journal is research in the field of Artificial Intelligence machine learning in health care & science, artificial intelligence, and advances, artificial intelligence in blockchain technology, artificial intelligence in healthcare, business, artificial neural networks, big data algorithms, big data analysis, cloud computing, computer vision, computer vision and perception, cyber defense, cyber security, data mining, data mining with big data, data science, decision management, deep learning, fleet management in Artificial Intelligence automation machine learning, humanoid robotics, image processing, perception internet of things, machine learning, machine learning, and computing, machines, and minds, mechatronics & nonlinear control systems (nolcos), multimedia technologies, natural language processing (NIP), neural system, robotic process automation (RPA), robotics, robots in security and surveillance, speech recognition, virtual intelligence, etc.

We welcome articles from Professors, Clinicians, Scientists, Research Scholars, and Medical Practitioners. We will publish all types of articles like Research Articles, Reviews, Short Communication, Commentary, Image Articles, PPTs, Letters to the Editor, and Editorials.

Submit the manuscript at www.opastpublishers.com/journal/advances-in-machine-learning-artificial-intelligence/manuscript-submission or send it as an e-mail attachment to the Editorial Office at info@opastpublishers.com

Advances in Machine Learning & Artificial Intelligence (ISSN: 2769-545X) is an online open-access journal that provides an advanced forum for articles related to Machine Learning & Artificial Intelligence. Following are some of the fields that the journal covers:

  • A/B testing
  • Accuracy
  • Activation Function
  • Advanced Algorithms
  • Algorithm
  • Anomaly Detection
  • Applications of Computer Science
  • Architecture Evaluations
  • Artificial General Intelligence (AGI)
  • Artificial intelligence
  • Artificial Narrow Intelligence (ANI)
  • Artificial Neural Network (ANN)
  • Augmented Reality
  • Automation and Mobile Robots
  • Bayesian Optimization
  • Bioengineering
  • Bioinformatics
  • Biometrics and Computer Forensics
  • Brain Mapping
  • Brain-inspired Intelligence
  • Brain-machine Interface
  • Chatbots
  • Clipping
  • Cloud Computing
  • Clustering
  • Cognitive computing
  • Cognitive Modeling of Intelligence
  • Computation and Language
  • Computational Biology
  • Computational Biology and Bio-informatics
  • Computational linguistics
  • Computational Statistics
  • Computer Applications
  • Computer Architecture
  • Computer Science and Game Theory
  • Computer Software / Hardware
  • Computer Vision
  • Computer Vision and Pattern Recognition
  • Computers and Society
  • Conversational Artificial Intelligence
  • Convolutional Neural Network (CNN)
  • Cryptography and Security
  • Cyber-Physical Systems
  • Data Engineering
  • Data Structures and Algorithms
  • Databases
  • Databases and Data mining
  • Deep Learning
  • Digital Ecosystem
  • Digital Libraries
  • Distributed, Parallel, and Cluster Computing
  • Document Analysis and Handwriting Recognition
  • Expert System
  • Generative Adversarial Networks (GAN)
  • Graphics
  • Heuristic
  • Human-Computer Interaction
  • Hybrid Artificial Intelligence
  • Image and Video Analysis
  • Image Processing
  • Information Retrieval
  • Information Theory
  • Intelligent Robotics
  • Internet Computing and Data Mining
  • Internet of Things (IOT)
  • Knowledge Representation and Reasoning
  • Learning
  • Logic in Computer Science
  • Machine Learning
  • Machine translation
  • Mechatronics
  • Multiagent Systems
  • Multimedia
  • Multimedia Analysis
  • Natural Language Processing (NLP)
  • Networking and Internet Architecture
  • Neural and Evolutionary Computing
  • Neural Networks
  • Numerical Analysis
  • Operating Systems
  • Optical Character Recognition (OCR)
  • Pattern Recognition
  • Performance
  • Post-quantum Cryptography
  • Programming Languages
  • Quantum Computing
  • Recurrent Neural Network (RNN)
  • Robotic Process Automation
  • Robotics
  • Security and Machine Learning
  • Soft Computing
  • Software Engineering
  • Sound
  • Speech and Language Processing
  • Virtual Intelligence