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Natural Transports-Inspired Differential Semantic Communications: Intelligent Transceivers Carry Just Differences as Meanings

Ali Taimori, Mathini Sellathurai, Tharmalingam Ratnarajah • IEEE Transactions on Machine Learning in Communications and Networking (2026)

Communication is a fundamental process in the nature of interconnected entities. Conventional engineering models of information transmission and reception, namely Shannon’s bit communication and Weaver’s semantic communication...

DOAJ Open Access (DOAJ) DOI: 10.1109/TMLCN.2026.3716920

Evolution of strategies in iterated games: a deep multi-agent reinforcement learning approach with hybrid genetic and CMA-ES optimization

ShangJun Li, Avijit Deb Nath, Md. Hadi Al-amin • Frontiers in Artificial Intelligence (2026)

The emergence of cooperation among self-interested agents in social dilemmas remains a central unsolved problem in evolutionary game theory, multi-agent systems, and behavioral science. While memory-one reciprocal strategies such as Tit-for...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1844089

Directions of application of artificial intelligence in digital marketing communications

O. V. Firsanova, S. V. Brovchak, V. V. Kulebyakin • Ученые записки Российской академии предпринимательства (2023)

The digital transformation of modern economic life has found its reflection in the field of marketing communications, having formed a virtually new form of communication between market entities-digital. A distinctive feature of this form is...

DOAJ Open Access (DOAJ) DOI: 10.24182/2073-6258-2023-22-2-132-139

SEMANTIC URBAN MESH SEGMENTATION BASED ON AERIAL OBLIQUE IMAGES AND POINT CLOUDS USING DEEP LEARNING

Ł. Wilk, Ł. Wilk, D. Mielczarek, W. Ostrowski et al. • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2022)

The use of deep machine learning methods for semantic classification of city mesh models is one of the current trends in geoscience development. Thanks to the thriving development of Convolutional Neural Networks (CNNs) it is now achievable...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLIII-B2-2022-485-2022

Prototype-oriented contrastive mean-teacher for unsupervised domain adaptive object detection

Qi Cao, Jianwen Tao, Yufang Dan, Di Zhou • Scientific Reports (2026)

Abstract Unsupervised domain adaptive object detection (UDA-OD) aims to deploy a detector trained on source domain(s) to a new, unlabeled target domain. Carrying out mean-teacher self-training for UDA-OD poses a significant challenge, given...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-44991-7

Economic Evaluations of Artificial Intelligence Implementation in Diabetic Retinopathy Screening

Ahmad Ahmad, Neily Zakiyah, Auliya A. Suwantika • Pharmacology and Clinical Pharmacy Research (2025)

Diabetic retinopathy (DR) is a common complication of diabetes that damages retinal blood vessels and can lead to vision impairment. The application of Artificial Intelligence (AI) in DR screening offers a promising alternative to conventio...

DOAJ Open Access (DOAJ) DOI: 10.15416/pcpr.v9i3.60068

AI-Driven Identification of Critical Dependencies in US-China Technology Supply Chains: Implications for Economic Security Policy

Guoli Rao, Chengru Ju, Zhen Feng • Journal of Advanced Computing Systems (2024)

This research examines the critical dependencies within US-China technology supply chains through advanced artificial intelligence methodologies, addressing significant economic security implications in an era of strategic competition. The ...

DOAJ Open Access (DOAJ) DOI: 10.69987/JACS.2024.41204