Transforming mining energy optimization: a review of machine learning techniques and challenges by Sravani Parvathareddy, Abid Yahya, Lilian Amuhaya, Ravi Samikannu, Raymond Sogna Suglo

“…The review identifies practical strategies to overcome these barriers, such as model compression for edge computing, federated learning for secure multi-site collaboration, and explainable AI for decision traceability. …”
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Learning efficient haptic shape exploration with a rigid tactile sensor array. by Sascha Fleer, Alexandra Moringen, Roberta L Klatzky, Helge Ritter

“…In the present work, we connect recent advances in recurrent models of visual attention with previous insights about the organisation of human haptic search behavior, exploratory procedures and haptic glances for a novel architecture that learns a generative model of haptic exploration in a simulated three-dimensional environment. …”
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Machine Learning-Based Security Solutions for IoT Networks: A Comprehensive Survey by Abdullah Alfahaid, Easa Alalwany, Abdulqader M. Almars, Fatemah Alharbi, Elsayed Atlam, Imad Mahgoub

“…This survey provides a comprehensive review of ML-driven IoT security solutions from 2020 to 2024, examining the effectiveness of supervised, unsupervised, and reinforcement learning approaches, as well as advanced techniques such as deep learning (DL), ensemble learning (EL), federated learning (FL), and transfer learning (TL). …”
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Deep Learning Approaches for Continuous Sign Language Recognition: A Comprehensive Review by Asma Khan, Seyong Jin, Geon-Hee Lee, Gul E. Arzu, L. Minh Dang, Tan N. Nguyen, Woong Choi, Hyeonjoon Moon

“…This classification serves as a helpful tool for researchers developing and organizing cutting-edge CSLR methods. The study highlights the effectiveness of deep learning systems in capturing different sign language signals. …”
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Advancements in Medical Radiology Through Multimodal Machine Learning: A Comprehensive Overview by Imran Ul Haq, Mustafa Mhamed, Mohammed Al-Harbi, Hamid Osman, Zuhal Y. Hamd, Zhe Liu

“…Potential future research directions are also identified. This review presents an overview of multimodal machine learning (MMML) in radiology, a field at the cutting edge of integrating artificial intelligence into medical imaging. …”
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Deep-Learning-Based Land Cover Mapping in Franciacorta Wine Growing Area by Girma Tariku, Isabella Ghiglieno, Andres Sanchez Morchio, Luca Facciano, Celine Birolleau, Anna Simonetto, Ivan Serina, Gianni Gilioli

“…This study addresses these gaps by presenting a methodology for semantic segmentation of land covers in agricultural areas using satellite images and deep learning models with pre-trained backbones. …”
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Multispectral Sensors and Machine Learning as Modern Tools for Nutrient Content Prediction in Soil by Rafael Felippe Ratke, Paulo Roberto Nunes Viana, Larissa Pereira Ribeiro Teodoro, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro, Dthenifer Cordeiro Santana, Carlos Eduardo da Silva Santos, Alan Mario Zuffo, Jorge González Aguilera

“…The combination of multispectral data and machine learning provides effective and flexible monitoring of the soil nutrient content, which consequently positively impacts plant productivity and food security, and ultimately promotes sustainable agricultural development overall. …”
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An efficient swarm evolution algorithm with probability learning for the black and white coloring problem by Zhiqiang Zhang, Li Zhang, Xiujun Zhang

“…This problem is a NP-complete problem, widely used in reagent product storage in chemical industry and the solution to the problem of black and white queens in chess. The paper presents a swarm evolution algorithm based on improved simulated annealing search and evolutionary operation with probability learning mechanism. …”
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Decentralized federated learning using validation loss for model sharing in crop disease classification by Denis Mamba Kabala, Adel Hafiane, Laurent Bobelin, Raphaël Canals

“…Several AI methods have been employed for this purpose, but despite achieving good results, many challenges remain, such as protecting farmers’ data, using machine learning on edge devices, and employing collaborative learning. …”
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SHM System for Composite Material Based on Lamb Waves and Using Machine Learning on Hardware by Gracieth Cavalcanti Batista, Carl-Mikael Zetterling, Johnny Öberg, Osamu Saotome

“…Moreover, NDT inspections are part of a more general structural health monitoring (SHM) system, where cutting-edge technologies are needed as powerful resources to achieve high performance. …”
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Exploration of Unsupervised Deep Learning-Based Gear Fault Detection for Wind Turbine Gearboxes by Bartłomiej Kiczek, Michał Batsch

“…This article presents a method for detecting surface damage on gear teeth using unsupervised machine learning. …”
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FedRSC: A Federated Learning Analysis for Multi-Label Road Surface Classifications by Ioannis V. Vondikakis, Ilias E. Panagiotopoulos, George J. Dimitrakopoulos

“…For this reason, it is important to analyze road conditions in order to improve traffic safety, optimize fuel efficiency, and provide a smoother travel experience. This research presents a federated learning analysis that brings together edge computing and cloud technology, by identifying various road conditions through a multi-label road surface classification analysis. …”
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Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…To address these challenges, we propose a novel multi-aircraft autonomous decision-making approach based on graphs and multi-agent reinforcement learning (MADRL) under zero-order optimization, implemented through the GraphZero-PPO algorithm. …”
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Research trends in the application of machine learning in sustainability practices based on a bibliometric analysis by Alejandro Valencia-Arias, Manuel Humberto Vásquez Coronado, Milagros Layesvka Clavo Medina, Maricarmen Jeneth Morales Garcia, Ana Rosa Requejo Arias, Josias Idelso Saavedra Tirado

“…The prevailing focus in this field has shifted towards the treatment of waste, the application of deep learning techniques, and the pursuit of sustainable development goals. …”
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Frontier machine learning techniques for melanoma skin cancer identification and categorization: An in-Depth review by Viomesh Singh, Kavita A. Sultanpure, Harshwardhan Patil

“…In this article we delve into a thorough exploration of cutting-edge machine learning methods that play a crucial role in identifying those sneaky signs of skin cancer. …”
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Emerging Trends in Machine Learning Assisted Optimization Techniques Across Intelligent Transportation Systems by Blessing Itoro Afolayan, Arka Ghosh, Jenny Fajardo Calderin, Antonio D. Masegosa

“…Model-based optimization approaches, reinforcement learning techniques, model-predictive control techniques, and generative AI techniques are the four areas into which this study divides AI optimization techniques for the sake of structure, clarity, and comparative analysis. …”
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Empowering machine learning for robust cyber-attack prevention in online retail: an integrative analysis by Kamran Razzaq, Mahmood Shah, Mohammad Fattahi, Jing Tang

“…Abstract Cyber-attack prevention in online retailing has proven to be a challenging task. Machine learning (ML) algorithms play a significant role in preventing cyber-attacks. …”
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Deep Federated Learning Based Convergence Analysis in Relaying-Aided MEC-IoT Networks by Jun Liu, Tao Cui, Lin Zhang, Yuwei Zhang, Jing Wang, Chao Li, Kai Chen, Huang Huang, Xuan Zhou, Wei Zhou, Sun Li, Suili Feng, Dongqing Xie, Yun Li, Haige Xiang, Kaimeno Dube, Abbarbas Muazu, Nakilavai Rono, Wen Zhou, Fusheng Zhu, Liming Chen, Dan Deng, Zhao Wang, Yajuan Tang

“…Recently, deep federated learning has attracted much attention from researchers in the fields of wireless communications, where the relaying technique has been shown as a powerful technology to assist the wireless signals and enhance the transmission quality, which is very important to the development of mobile edge computing (MEC) based Internet of Things (IoT) networks. …”
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Federated Learning for privacy-Friendly Health Apps: A Case Study on Ovulation Tracking by Nikolaos Pavlidis, Andreas Sendros, Theodoros Tsiolakis, Periklis Kostamis, Christos Karasoulas, Eleni Briola, Christos Chrysanthos Nikolaidis, Vasilis Perifanis, George Drosatos, Eleftheria Katsiri, Despoina Elisavet Filippidou, Anastasios Manos, Pavlos S. Efraimidis

“…Health applications often need to balance advanced AI functionalities with sufficient privacy measures to ensure user engagement. This paper presents the architecture of FLORA, a privacy-first ovulation-tracking application that leverages federated learning (FL), privacy-enhancing technologies (PETs), and blockchain to protect user data while delivering accurate and personalized health insights. …”
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Hyperspectral Anomaly Detection Using Dual-Branch Network Based on Frequency Domain Learning by Xiaoyi Wang, Jun Du, Qingxuan Lv, Peng Wang, Xianchao Zhang, Jian Cheng, Henry Leung

“…To resolve these challenges, this article presents a dual-branch network based on frequency domain learning. …”
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