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Multi‐modal broad learning for material recognition

Zhaoxin Wang, Huaping Liu, Xinying Xu, Fuchun Sun • Cognitive Computation and Systems (2021)

Abstract Material recognition plays an important role in the interaction between robots and the external environment. For example, household service robots need to replace humans in the home environment to complete housework, so they need t...

DOAJ Open Access (DOAJ) DOI: 10.1049/ccs2.12004

Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture

B.S. Prashanth, Manoj Kumar, Ariful Hoque, Nasser Al Muraqab et al. • International Review of Economics & Finance (2026)

The development of online banking has brought about an increase in fraudulent operations, which is a major problem for banks. This study delves into the urgent requirement for interpretable, scalable, and top-notch fraud detection systems b...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iref.2026.104916

Explainable artificial intelligence: A survey

Filip Karlo Došilović, Mario Brčić, Nikica Hlupić • International Convention on Information and Communication Technology, Electronics and Microelectronics (2018)

In the last decade, with availability of large datasets and more computing power, machine learning systems have achieved (super)human performance in a wide variety of tasks. Examples of this rapid development can be seen in image recognitio...

OPENALEX DOI: https://doi.org/10.23919/mipro.2018.8400040

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

Evolutionary Grey Wolf Optimizer with Cross-Search and Memory Mechanisms for Complex Optimization Problems

Hoda Zamani, Mohammad H. Nadimi-Shahraki, Seyedali Mirjalili • International Journal of Computational Intelligence Systems (2026)

Abstract —Large-scale engineering optimization problems, characterized by hundreds or thousands of decision variables, complex constraints, and highly nonlinear objective functions, present significant challenges for conventional optimizati...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-026-01291-2

Tailoring industrial enzymes for thermostability and activity evolution by the machine learning-based iCASE strategy

Nan Zheng, Yongchao Cai, Zehua Zhang, Huimin Zhou et al. • Nature Communications (2025)

Abstract The pursuit of obtaining enzymes with high activity and stability remains a grail in enzyme evolution due to the stability-activity trade-off. Here, we develop an isothermal compressibility-assisted dynamic squeezing index perturba...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41467-025-55944-5

Artificial Intelligence Voluntary Disclosures and Their Effect on Firms’ Financial Performance: Evidence from Egypt Firms on the EGX30 Index

suzy elnokoudy • المجلة العلمية للدراسات والبحوث المالية والتجارية (2025)

The present paper, thus, investigates the link between AI-disclosure in annual reports and firm performance in the Egyptian financial industry. It explains how the number of appertained AI-words in the corporate disclosures would correspond...

DOAJ Open Access (DOAJ) DOI: 10.21608/cfdj.2024.326666.2065

Design of the Digital Pathology Workspace for Artificial Intelligence Integration

Elena Guerini-Rocco, Chiara Frascarelli, Joana Sorino, Francesca Maria Porta et al. • Applied Sciences (2026)

Designing an optimal digital pathology workspace is essential to ensure diagnostic accuracy and safeguard the long-term well-being of pathologists. While digital pathology improves reproducibility, facilitates multidisciplinary collaboratio...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16126021

Expert Agents for Social and Emotional Learning: An Agentic Graph Retrieval Augmented Generation Approach

Eleni Fotopoulou, Anastasios Zafeiropoulos, Eleftheria Arkadopoulou, Christina-Maria Androna et al. • IEEE Access (2026)

The positive impact of Social and Emotional Learning (SEL) activities in schools is widely recognized in various sectors, including mental health, social relationships, and academic performance of students. This impact can be efficiently re...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2026.3671870

Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification

Jiayun Xin, Mohammad Khishe, Diyar Qader Zeebaree, Laith Abualigah et al. • Heliyon (2024)

Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeog...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2024.e28147

MP-VHPPI: Meta predictor for viral host protein-protein interaction prediction in multiple hosts and viruses

Muhammad Nabeel Asim, Muhammad Nabeel Asim, Ahtisham Fazeel, Ahtisham Fazeel et al. • Frontiers in Medicine (2022)

Viral-host protein-protein interaction (VHPPI) prediction is essential to decoding molecular mechanisms of viral pathogens and host immunity processes that eventually help to control the propagation of viral diseases and to design optimized...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2022.1025887

Association between phthalate exposure and accelerated bone maturation in Chinese girls with early puberty onset: a propensity score-matched case–control analysis

Shurong Huang, Zhe Su, Huiping Su, Yanhua Jiao et al. • Scientific Reports (2022)

Abstract Estrogen can promote the acceleration of bone maturation and phthalate esters (PAEs) have estrogen-mimicking effects. We investigated whether PAEs are associated with the acceleration of bone age (BA) in girls with early onset of p...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-022-19470-4

Development of a BIM-based AI-driven matching tool for LCA datasets

Dino Petrosa, Pamela Haverkamp, Jana Gerta Backes, David Crampen et al. • Discover Sustainability (2025)

Abstract The construction sector significantly contributes to environmental issues and often relies on Life Cycle Assessment (LCA) for the quantification and optimization of its environmental impacts. One of the most time- and labour-intens...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-025-02203-8

A multi-organization epigenetic age prediction based on a channel attention perceptron networks

Jian Zhao, Haixia Li, Jing Qu, Jing Qu et al. • Frontiers in Genetics (2024)

DNA methylation indicates the individual’s aging, so-called Epigenetic clocks, which will improve the research and diagnosis of aging diseases by investigating the correlation between methylation loci and human aging. Although this discover...

DOAJ Open Access (DOAJ) DOI: 10.3389/fgene.2024.1393856