Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…Additionally, transfer learning and attention mechanisms have been instrumental in enhancing the precision and speed of defect detection, enabling real-time applications. Notable approaches like YOLO (You Only Look Once) and its variants have shown exceptional performance in detecting defects with varying scales and complexities, leveraging innovations such as feature pyramid networks and efficient loss functions. …”
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Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

“…The research article addresses this gap by introducing the Temporal Adaptive Neural Evolutionary Algorithm (TANEA), a novel approach designed to enhance the predictive capabilities in biomedical IoT systems. …”
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Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

“…However, the accuracy and convergence speed of existing defect detection techniques still require improvement. In this paper, an improved algorithm based on YOLOv8n was designed for accurate detection of wood panel defects. …”
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Advancing Image Forensic: Detecting Facial Manipulations via Meso_KNN by Hazem Issa, Bayan Zarnahji

“…What distinguishes this model is its focus on important features in facial images that represent vital characteristics of facial manipulation. …”
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Evaluation Method for Running State of Electricity Meters Based on Random Matrix Theory and Clustering Algorithm by Yingying CHENG, Jie DU, Quan ZHOU, Jiaming ZHANG, Xiaoyong ZHANG, Gang LI

“…Further, an improved DTW (dynamic time warping) clustering algorithm is used to analysis the linear feature statistics of the output of the random matrix. …”
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Plasticulture detection at the country scale by combining multispectral and SAR satellite data by Alessandro Fabrizi, Peter Fiener, Thomas Jagdhuber, Kristof Van Oost, Florian Wilken

“…., greenhouse, tunnel) across Germany. The algorithm detected 103 103 ha of PMF and 37 103 ha of PCV in 2020, while a combination of agricultural statistics and surveys estimated a smaller plasticulture cover of around 100 103 ha in 2019. …”
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DMCM: Dwo-branch multilevel feature fusion with cross-attention mechanism for infrared and visible image fusion. by Xicheng Sun, Fu Lv, Yongan Feng, Xu Zhang

“…In response to the limitations of current infrared and visible light image fusion algorithms-namely insufficient feature extraction, loss of detailed texture information, underutilization of differential and shared information, and the high number of model parameters-this paper proposes a novel multi-scale infrared and visible image fusion method with two-branch feature interaction. …”
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GNSS-Based Multi-Target RDM Simulation and Detection Performance Analysis by Jinxing Li, Qi Wang, Meng Wang, Youcheng Wang, Min Zhang

“…Furthermore, we introduce an Unscented Particle Filter (UPF) algorithm for dynamic target tracking and state estimation. …”
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An Enhanced Deep Learning Model for Effective Crop Pest and Disease Detection by Yongqi Yuan, Jinhua Sun, Qian Zhang

“…Traditional machine learning methods struggle with plant pest and disease image recognition, particularly when dealing with small sample sizes, indistinct features, and numerous categories. This paper proposes an improved ResNet34 model (ESA-ResNet34) for crop pest and disease detection. …”
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Advanced intrusion detection in internet of things using graph attention networks by Aamir S. Ahanger, Sajad M. Khan, Faheem Masoodi, Ayodeji Olalekan Salau

“…In this paper, we present a novel perspective to IoT security by using a Graph-based (GB) algorithm to construct a graph that is evaluated with a graph-based learning Intrusion Detection System (IDS) incorporating a Graph Attention Network (GAT). …”
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Hybrid adaptive method for lane detection of degraded road surface condition by Khaled H. Almotairi

“…Subsequently, numerical features about the boundaries of the candidate lanes are extracted and used by a model of the k-nearest neighbor algorithm and the Gaussian process for final lane discovery. …”
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Bottom Detection Method of Side-Scan Sonar Image for AUV Missions by Huapeng Yu, Ziyuan Li, Dailin Li, Tongsheng Shen

“…In order to obtain the measurement parameters of the sea bottom geomorphology or underwater objects, the first step in side-scan sonar (SSS) image processing is bottom detection. Due to the complexity of the marine environment, the acoustic signals received by SSS are usually polluted by noises, which affect its image quality and make the extraction of image features difficult. …”
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Improvement of RT-DETR model for ground glass pulmonary nodule detection. by Siyuan Tang, Qiangqiang Bao, Qingyu Ji, Tong Wang, Naiyu Wang, Min Yang, Yu Gu, Jinliang Zhao, Yuhan Qu, Siriguleng Wang

“…This article proposed an algorithm based on RT-DETR model with the following enhancement: 1) optimize the backbone network with FCGE blocks to increase the detection accuracy of small-sized and blurred edge nodules; 2) replace the AIFI module with HiLo-AIFI module to reduce redundant computation and improve the detection accuracy of pure ground glass pulmonary nodules and mixed ground glass pulmonary nodules; 3) replace the DGAK module with CCFF module to address the issue of capturing complex features and recognition of irregularly shaped ground glass nodules. …”
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AI-driven genetic algorithm-optimized lung segmentation for precision in early lung cancer diagnosis by Yahia Said, Riadh Ayachi, Mouna Afif, Taoufik Saidani, Saleh T. Alanezi, Oumaima Saidani, Ali Delham Algarni

“…Lung segmentation plays a pivotal role in the diagnostic pipeline, directly impacting the accuracy of disease detection and treatment planning. This study presents an advanced AI-driven framework, optimized through genetic algorithms, for precise lung segmentation in early cancer diagnosis. …”
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Ensemble Algorithm Based on Gene Selection, Data Augmentation, and Boosting Approaches for Ovarian Cancer Classification by Zne-Jung Lee, Jing-Xun Cai, Liang-Hung Wang, Ming-Ren Yang

“…In the proposed approach, the initial genetic data were first subjected to feature selection. <b>Results:</b> The target genes were screened and combined with data augmentation and ensemble boosting algorithms. …”
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System Architecture for Real-Time Face Detection on Analog Video Camera by Mooseop Kim, Deokgyu Lee, Ki-Young Kim

“…The proposed architecture is based on AdaBoost learning algorithm with Haar-like features and it aims to apply face detection to a low-cost FPGA that can be applied to a legacy analog video camera as a target platform. …”
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Steel surface defect detection method based on improved YOLOv9 by Cong Chen, Hoileong Lee, Ming Chen

“…Second, the C3 module is incorporated to effectively fuse feature maps from different levels, enhancing the model’s ability to detect multi-scale targets. …”
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YOLOv9-GSSA model for efficient soybean seedlings and weeds detection by Baihe Liang, Liangchen Hu, Guangxing Liu, Peng Hu, Shaosheng Xu, Biao Jie

“…Challenges include the small size and morphological similarity of seedlings and weeds, complicating conventional detection methods. To tackle these issues, we propose a real-time detection algorithm called YOLOv9-GSSA. …”
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Bilingual hate speech detection on social media: Amharic and Afaan Oromo by Teshome Mulugeta Ababu, Michael Melese Woldeyohannis, Emuye Bawoke Getaneh

“…According to the experiment, BiLSTM with FastText feature extraction is an outperforming the other algorithm by achieving a 78.05% accuracy for Bilingual Amharic Afaan Oromo hate speech detection. …”
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Automatic Paddy Planthopper Detection and Counting Using Faster R-CNN by Siti Khairunniza-Bejo, Mohd Firdaus Ibrahim, Marsyita Hanafi, Mahirah Jahari, Fathinul Syahir Ahmad Saad, Mohammad Aufa Mhd Bookeri

“…Therefore, this research presents a comprehensive assessment of an object detection algorithm specifically developed to precisely detect and quantify planthoppers. …”
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