Integrated data-driven topology reconstruction and risk-aware reconfiguration for resilient power distribution systems under incomplete observability by Sipei Sun, Ning Li, Liang Zhang, Dongpo Zhao, Di Lun, Liang Feng

“…Abstract This paper proposes a unified data-driven framework for topology identification, risk quantification, and reconfiguration optimization in power distribution networks under incomplete and fragmented observability. …”
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Segmentation of Stone Slab Cracks Based on an Improved YOLOv8 Algorithm by Qitao Tian, Runshu Peng, Fuzeng Wang

“…To tackle the challenges of detecting complex cracks on large stone slabs with noisy textures, this paper presents the first domain-optimized framework for stone slab cracks, an improved semantic segmentation model (YOLOv8-Seg) synergistically integrating U-NetV2, DSConv, and DySample. …”
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Enhance differential privacy mechanisms for clinical data analysis using CNNs and reinforcement learning by Rakesh Batchala, Priyank Jain, Manasi Gyanchandani, Sanyam Shukla, Rajesh Wadhvani

“…Abstract This work proposes a novel approach that provides a comparative reinforcement learning framework for clinical decision-making in critical care situations. …”
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Small object detection in side-scan sonar images based on SOCA-YOLO and image restoration by Xiaodong Cui, Jiale Zhang, Lingling Zhang, Qunfei Zhang, Jing Han

“…The SOCA-YOLO framework first constructs a high-resolution SSS (sidescan sonar image) enhancement pipeline through image restoration techniques to extract fine-grained features of micro-scale targets. …”
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Latent Graph Attention for Spatial Context in Light-Weight Networks: Multi-Domain Applications in Visual Perception Tasks by Ayush Singh, Yash Bhambhu, Himanshu Buckchash, Deepak K. Gupta, Dilip K. Prasad

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DB-Net: A Dual-Branch Hybrid Network for Stroke Lesion Segmentation on Non-Contrast CT Images by Xiao Jia, He Dong, Jiashu Xu, Yanhong Zhang, Yihua Lan

“…To address these challenges, this study proposes a two-branch hybrid network combining a convolutional neural network (CNN) with a Transformer framework. …”
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An Innovative Artificial Intelligence Classification Model for Non-Ischemic Cardiomyopathy Utilizing Cardiac Biomechanics Derived from Magnetic Resonance Imaging by Liqiang Fu, Peifang Zhang, Liuquan Cheng, Peng Zhi, Jiayu Xu, Xiaolei Liu, Yang Zhang, Ziwen Xu, Kunlun He

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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…The proposed research combines MobileNet and VGG16 to build a transfer learning (TL) principles-based framework named FruitsMultiNet. These models were chosen because they achieved the highest individual accuracy compared to other models. …”
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Federated duelling deep Q‐network based collaborative energy scheduling for a power distribution network by Yanhong Yang, Wei Pei, Tianyi Xu, Dawei Wang, Abdelbari Redouane

“…In this study, a federated deep reinforcement learning framework was developed to facilitate collaborative energy scheduling and maximize the total economic benefit in a distribution network. …”
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YOLO Object Detection for Real-Time Fabric Defect Inspection in the Textile Industry: A Review of YOLOv1 to YOLOv11 by Makara Mao, Min Hong

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PDCG-Enhanced CNN for Pattern Recognition in Time Series Data by Feng Xie, Ming Xie, Cheng Wang, Dongwei Li, Xuan Zhang

“…It proposes a Pattern-Driven Case Generator (PDCG) framework to automate the creation of labeled time series data for training CNN models, addressing the challenge of manual dataset curation. …”
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CMHFE-DAN: A Transformer-Based Feature Extractor with Domain Adaptation for EEG-Based Emotion Recognition by Manal Hilali, Abdellah Ezzati, Said Ben Alla

“…This paper presents a novel end-to-end deep learning framework for EEG-ER, combining temporal feature extraction, self-attention mechanisms, and adversarial domain adaptation. …”
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Classification of Multiple Partial Discharge Sources Using Time-Frequency Analysis and Deep Learning by Awad Almehdhar, Radek Prochazka

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Intention Recognition for Multiple AUVs in a Collaborative Search Mission by Yinhuan Wang, Kaizhou Liu, Lingbo Geng, Shaoze Zhang

“…We propose a consensus-based intent recognition (CBIR) method grounded in the Belief–Desire–Intention (BDI) framework. The CBIR approach incorporates fuzzy inference and deep learning techniques to predict AUV intentions with minimal data exchange, improving the robustness and efficiency of collaborative decision making. …”
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Development of approach to an automated acquisition of static street view images using transformer architecture for analysis of Building characteristics by Seunghyeon Wang

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A Multi-Area Software-Defined Vehicular Network Control Plane Deployment Mechanism Oriented to Traffic Prediction by Hao Li, Hongming Li, Yuqing Ji, Ziwei Wang

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Landfill Site Suitability Assessment Based on GIS and Multicriteria Analysis: A Case Study of Kirkuk City by Hana Kareem Shekho, Muntadher Aidi Shareef

“…The technique provides a framework for assessing the appropriateness of dump sites in various geographical areas. …”
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Identification of Nanoparticle Agglomeration in Polymer Plates Reinforced with Carbon Nanotubes by Use of Active Thermography and Deep Learning-Based Image Processing by Mazharul Islam, Raihan Sarker

“…An eight-layer DCNN framework was implemented using three different window sizes of 41×41, 51×51, and 61×61 pixels, which was trained using 175,598 segments of images, of which 85% was made available for training, while 15% was used for evaluation. …”
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Ai-powered digital twin in the industrial IoT by Željko Bolbotinović, Saša D. Milić, Žarko Janda, Dragan Vukmirović

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TinyML-Based Real-Time Drift Compensation for Gas Sensors Using Spectral–Temporal Neural Networks by Adir Krayden, M. Avraham, H. Ashkar, T. Blank, S. Stolyarova, Yael Nemirovsky

“…We present a real-time drift compensation framework based on a lightweight Temporal Convolutional Neural Network (TCNN) combined with a Hadamard spectral transform. …”
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