Early Detection of Alzheimer’s Disease: An Extensive Review of Advancements in Machine Learning Mechanisms Using an Ensemble and Deep Learning Technique by Renjith Prabhavathi Neelakandan, Ramesh Kandasamy, Balasubramani Subbiyan, Mariya Anto Bennet

“…The findings of this study contribute significantly to the field of AD diagnoses and pave the way for more precise and efficient early detection strategies.…”
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Synthesis of Rhodamine TEMPO Conjugates via Isonitrile‐Based Multicomponent‐Reactions for Mitochondria‐Targeted ROS‐Detection in Cancer Cells by Haider N. Sultani, Ibrahim M. Morgan, Hidayat Hussain, Haleh H. Haeri, Dariush Hinderberger, Goran N. Kaluđerović, Bernhard Westermann

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Optimized small object detection in low resolution infrared images using super resolution and attention based feature fusion. by Weilun Wang, Jian Xu, Ruopeng Zhang

“…Infrared (IR) imaging is extensively applied in domains such as object detection, industrial monitoring, medical diagnostics, intelligent transportation due to its robustness in low-light, adverse weather, and complex environments. …”
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Design of a novel noise resilient algorithm for fault detection in wind turbines on supervisory control and data acquisition system by Muhammad Irfan, Nabeel Ahmed Khan, Muhammad Abubakar, Zohaib Mushtaq, Tomasz Jakubowski, Paweł Sokołowski, Grzegorz Nawalany, Saifur Rahman

“…Hence, timely detection of these operational anomalies is crucial for optimizing performance and reducing maintenance costs. …”
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DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification by Musa Adamu Wakili, Harisu Abdullahi Shehu, Mahdi Abdollahi, Badamasi Imam Ya'u, Md Haidar Sharif, Huseyin Kusetogullari

“…While histopathological image analysis plays a key role in breast cancer diagnosis, the complexity and heterogeneity of these images present significant challenges. …”
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A novel YOLOv11-Driven deep learning algorithm for UAV multispectral oil spill detection in Inland lakes by Yu Zhang, Jian Xing, Weida Chen, Haitao Wang, Bingyu Shi, Yang Song, Xiaoou Huang, Zihan Jiang

“…Abstract Lake oil spills are challenging to detect accurately due to complex oil–water interactions resulting from water flow disturbances, vegetation occlusion, and the diffusion behavior of oil films. …”
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DGS-Yolov7-Tiny: a lightweight pest and disease target detection model suitable for edge computing environments by Ping Yu, Baoshu Zong, Xiaozhong Geng, Hui Yan, Baijin Liu, Cheng Chen, Hupeng Liu, Xiaoqing Xu

“…However, traditional object detection models are often computationally intensive and complex, rendering them unsuitable for real-time applications in edge computing. …”
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FD²-YOLO: A Frequency-Domain Dual-Stream Network Based on YOLO for Crack Detection by Junwen Zhu, Jinbao Sheng, Qian Cai

“…However, most existing methods use multi-scale and attention mechanisms to improve on a single backbone, and this single backbone network is often ineffective in detecting slender or variable cracks in complex scenarios. …”
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SD-YOLOv8: SAM-Assisted Dual-Branch YOLOv8 Model for Tea Bud Detection on Optical Images by Xintong Zhang, Dasheng Wu, Fengya Xu

“…This demonstrates its superior capability in efficiently detecting tea buds against complex backgrounds. …”
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Parameter Disentanglement for Diverse Representations by Jingxu Wang, Jingda Guo, Ruili Wang, Zhao Zhang, Liyong Fu, Qiaolin Ye

“…PDDR can be seamlessly integrated into modern networks, significantly improving the learning capacity of a network while maintaining the same complexity for inference. Experimental results show great improvements on various tasks, with an improvement of 1.47% over Residual Network 50 (ResNet50) on ImageNet, and we improve the detection results of Retina Residual Network 50 (Retina-ResNet50) by 1.7% Mean Average Precision (mAP). …”
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A human pose estimation network based on YOLOv8 framework with efficient multi-scale receptive field and expanded feature pyramid network by Shaobin Cai, Han Xu, Wanchen Cai, Yuchang Mo, Liansuo Wei

“…Abstract Deep neural networks are used to accurately detect, estimate, and predict human body poses in images or videos through deep learning-based human pose estimation. …”
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An efficient trustworthy cyberattack defence mechanism system for self guided federated learning framework using attention induced deep convolution neural networks by Louai A. Maghrabi, Alanoud Subahi, Nouf Atiahallah Alghanmi, Turki Althaqafi, Nahla J. Abid, Nasser N. Albogami, Mahmoud Ragab

“…Abstract As cyberattacks become more advanced, conventional centralized threat intelligence models often fail to keep up with these threats’ growing complexity and frequency, highlighting the requirement for innovative approaches to strengthen cybersecurity resilience. …”
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Multi-Modal Dynamic Fusion for Defect Detection in Electronic Products: A Novel Approach Based on Energy and Deep Learning by Yulin Liu, Yang Gao

“…Conventional defect detection approaches, which typically depend on a single modality, often fall short in both efficiency and reliability. …”
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A hybrid machine learning model for intrusion detection in wireless sensor networks leveraging data balancing and dimensionality reduction by Md. Alamin Talukder, Majdi Khalid, Nasrin Sultana

“…This hybrid approach addresses class imbalance and high-dimensionality challenges, providing scalable and robust intrusion detection. Complexity analysis reveals that the proposed model reduces training and prediction times, making it suitable for real-time applications.…”
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Comparative analysis of data-driven models on detection and classification of electrical faults in transmission systems: Explainability, applicability and industrial implications by Chibueze D. Ukwuoma, Dongsheng Cai, Chiagoziem C. Ukwuoma, Chinedu I. Otuka, Qi Huang

“…Most data-driven fault detection methods often face challenges in accuracy, adaptability, and real-time implementation, particularly in complex transmission networks. …”
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City Logistics Solutions for CO₂ Emission Reduction and Energy Efficiency: A Comparative Study of Vitoria-Gasteiz, Tartu, and Sønderborg by Joanna Rut, Wiktoria Dziki, Ryszard Beniak, Michal Podpora, Arkadiusz Gardecki, Bartlomiej Klin

“…In a time of continuous urbanization, with more than half of the world’s population living in cities, city logistics plays a crucial role in managing complex urban environments. As part of the concept of sustainable development, city logistics aims to minimize the negative impact of transport on the environment, while increasing operational efficiency and improving the comfort of life of residents in urban agglomerations. …”
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Golden Chip-Free Hardware Trojan Detection Using Attention-Based Non-Local Convolution With Simple Recurrent Unit by Rama Devi Maddineni, Deepak Ch

“…The emergence of machine learning and deep learning models has enhanced the feasibility of hardware Trojan detection, as these models can learn complex patterns and representations from extensive datasets. …”
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A Small-Sample Target Detection Method of Side-Scan Sonar Based on CycleGAN and Improved YOLOv8 by Ye Zheng, Jun Yan, Junxia Meng, Ming Liang

“…Because of their low cost and ease of deployment, side-scan sonars is one of the most widely used underwater survey instruments. However, the complexity of the marine environment and the difficulty in target acquisition limit the detection accuracy of side-scan sonars. …”
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Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images by Chi-en Amy Tai, Elizabeth Janes, Chris Czarnecki, Alexander Wong

“…A recent movement for TinyML applications is integrating Double-Condensing Attention Condensers (DC-AC) into a self-attention neural network backbone architecture to allow for faster and more efficient computation. This paper explores leveraging an efficient self-attention structure to detect skin cancer in skin lesion images and introduces a deep neural network design with DC-AC customized for skin cancer detection from skin lesion images. …”
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Proposal for an Intelligent Methodology to Manage Energy in Buildings and Detect Anomalies as a Compass Towards Zero Energy Buildings (ZEB) by Irati Prol-Godoy, Roberto Santana, Francisco-Javier Rey-Martinez, Ana Picallo-Perez

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