ISSN Print: 0000-0000
ISSN Online: 0000-0000 Impact Factor 2022
(Based on Google scholar citation)

i-manager's Journal on Artificial Intelligence & Machine Learning (JAIM)

Simulating Human Intelligence into Machines

Aims and Scope

Inspired by nature and with the ever growing abundance of data, computer science technologists, engineers and scientists devised several algorithms to make the computer intelligent as humans, to draw inferences, to reveal hidden patterns, to make decisions, to visualize the data, to recognize and distinguish, to listen, to construct visual models and to control unmanned systems with decision support, etc. i-manager’s Journal on Artificial Intelligence and Machine Learning aims in bringing the researches in the advancements of nature inspired and bionic algorithms, supervised and unsupervised machine learning, with applications in education, healthcare, aviation, unmanned vehicles, machine design, design and modelling, industrial automation, industrial safety, military and warfare applications, night vision and guidance, logistics, safety and security applications, disaster rescue, animation series, recommender systems in online business, personalized learning and career guidance systems, etc. This Journal will bridge the academicians, researchers and entrepreneurs with the corporates focused on product development.

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Publication Ethics and Malpractice Statement

We follow stringent publication ethics, and plagiarized papers are not published, and are withdrawn at any stage of the publishing process. Plagiarism is not limited to the Results and Discussion sections; it can involve any part of the manuscript, including figures and tables, in which material is copied from another publication without attestation, reference, or permission.

Publication Ethics & Peer Review Policy

i-manager Publications follow transparent policies right from paper submission to publication through various well defined and time tested processes.

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Review Procedure

The Journal follows a double blind peer-review process. The submitted articles / research papers are reviewed by Professors/Educators in Engineering fields.

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Overall Topics Covered

  • Cognitive Science

  • Computational Neural Networks and Artificial Neural Networks (ANN)

  • Deep Learning

  • Deep Learning and Neural Networks with Keras

  • Semantic Analysis

  • Supervised and Unsupervised Learning

  • Computer Vision

  • Natural Language Processing, Understanding and Generation (NLP, NLU & NLG)

  • Overfitting

  • Bias-Variance Trade Off

  • Classification, Clustering, Regression and Association

  • Gradient Descent Algorithm

  • Decision Trees

  • Support Vector Machines (SVM)

  • Evolutionary Algorithms and Algorithm Development for Improved AI and ML

  • Generative Adversarial Networks

  • Bioinspired Intelligence

  • Biomimetic and Evolutionary Techniques

  • Deep Learning with Biomimicry

  • Neuromorphic Computing

  • Deep Learning with TensorFlow

  • AI Initiatives and Ethical Standards