Editorial to the Inaugural Issue

Dear editors, reviewers, authors, readers, and other members of the whole scientific and professional community,

Welcome to this inaugural issue of the Acadlore Transactions on AI and Machine Learning (ATAIML).

Artificial intelligence and machine learning changed in the last 10 years to emerging technologies, which are in the focus of academic and applied research as powerful applications in industries, agriculture, health, service and culture sectors as well. Together with next-generation computing, metaverse and other areas, they shape our digital Future.

According to the Gartner report about emerging AI trends

- Democratizing AI

- Combining different AI techniques to improve the efficiency of learning

- Using AI techniques embedded in Internet of Things (IoT) technologies

- Making appropriate business and ethical choices when adopting AI and

- Developing AI techniques that learn a representation of artifacts from the data and using them to generate completely original artifacts are the emerging trends for AI development in the next years.

Acadlore Transactions on AI and Machine Learning (ATAIML) is a new open access journal of computer science, artificial intelligence, machine and deep learning, graph neural networks, synthetic data and other related fields. It covers theory, methods and interdisciplinary applications, algorithms, data and implementations on different platforms. It is embedded in a family of publication platforms which support the above-mentioned trends and offers an advanced meeting place for studies related to AI and machine learning topics and their applications. The journal will have a special focus on the relation between AI and extended reality, to synthetic data and to graph neural networks.

This new journal focuses on (in an alphabetical order)

• AI and design, fashion and arts

• AI and IoT

• AI and mixed reality and multimedia data

• AI and psychology

• AI and smart food, agriculture and forest

• Data-centric AI and synthetic data

• Ethical and law issues of AI

• Graph neural networks

• Machine Learning in medicine, biology, chemistry, physics

• Statistical and topological methods in machine learning

but not only.

In our first issue we present seven papers, related to deep learning applications in medicine, traffic security, cinematography and real estate business.

The used algorithms are well known in the community and adapted according to the requirements of the related application. They cover semantic analysis, feature selection, image segmentation with U-nets and computer vision.

The authors are coming from India, China, Cameroon, Indonesia. We see this as a contribution to develop our journal as a world open journal, supporting scientists especial also from emerging countries.

We commend these articles to the readership and hope for much feedback.