Research on the Application of Deep Learning Algorithm in the Damage Detection of Steel Structures by Qingyun Ge, Caimei Li, Fulian Yang

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Morphological Edge Detection Algorithm of Colon Pathological Sections Based on Shearlet by Shasha Li, Caixia Deng, Tong Wang, Zhaoru Zhang

“…This algorithm is used to carry out the edge detection of images after denoising yields a new edge detection algorithm that fuses the Meyer Shearlet denoising and mathematical morphology. …”
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Workflow for effective integration of community detection algorithms in brain network analysis by Flavio Averhoff, Vladimir Aristov, Ivan Stepanyan, Chen Yunwei, Jorge Gulín González

“…An autoencoder model was employed to analyze functional connectivity networks, and the Louvain algorithm was used to detect communities within these networks. …”
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Lightweight remote sensing ship detection algorithm based on YOLOv5s by Haochen WANG, Yuelan XIN, Jiang GUO, Qingqing WANG

“…ObjectiveThis paper proposes a lightweight remote sensing ship target detection algorithm LR-YOLO based on improved YOLOv5s to meet the lightweight and fast inference requirements of ship target detection tasks involving remote sensing images. …”
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Fault Detection of Aircraft Control System Based on Negative Selection Algorithm by Jie Chen, Senyao Chen, Cunbao Ma, Zhengdong Jing, Qingshan Xu

“…In this paper, by taking advantage of the strong leaning and intelligent recognition ability and the characteristic of less information required in the negative selection artificial immune system, a fault detection method is proposed for aircraft control system based on negative selection algorithm. …”
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Overlapping Box Suppression and Merging Algorithms for Window-Based Object Detection by Kos Aleksandra

“…In this manuscript, we extend the Overlapping Box Suppression (OBS) algorithm, a novel approach designed to enhance window-based object detection systems by reducing false-positive detections. …”
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Congestion control algorithm based on jitter detection in metro Ethernet networks by HAO Jun-rui1, YU Shao-hua1

“…A novel congestion control algorithm （JDCC） for multimedia traffics was proposed. …”
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Study on lightweight strategies for L-YOLO algorithm in road object detection by Ji Hong, Kuntao Ye, Shubin Qiu

“…The demand for real-time, efficient object detection systems is growing. However, traditional algorithms often suffer from large parameter sizes and high computational costs, limiting their applicability in resource-constrained environments. …”
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A feature enhancement FCOS algorithm for dynamic traffic object detection by Tuqiang Zhou, Wei Liu, Haoran Li

“…The Fully Convolutional One-Stage (FCOS) object detection algorithm was used as baseline. First, the dynamic convolution module was designed in the backbone network to identify different object features to the maximum extent. …”
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Group Abnormal Behaviour Detection Algorithm Based on Global Optical Flow by Yu Hao, Ying Liu, Jiulun Fan, Zhijie Xu

“…Abnormal behaviour detection algorithm needs to conduct behaviour analysis on the basis of continuous video inclination tracking, and the robustness of the algorithm is reduced for the occlusion of moving targets, the occlusion of the environment, and the movement of targets with the same colour. …”
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Machine fault detection model based on MWOA-BiLSTM algorithm by Yi-Qiang Xia, Yang Yang

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PSO–SOM Neural Network Algorithm for Series Arc Fault Detection by Na Qu, Jiatong Chen, Jiankai Zuo, Jinhai Liu

“…In this paper, the particle swarm optimization (PSO) algorithm is used to optimize the weight values of SOM network. …”
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Mine underground object detection algorithm based on TTFNet and anchor-free by Song Zhen, Qing Xuwen, Zhou Meng, Men Yuting

“…To solve the problem of poor object detection effect caused by uneven light and high noise in underground mines, this study proposes a TTFNet (training-time-friendly network)-based object detection algorithm for underground mines. …”
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A Suggested Point Search Algorithm for Circle Detection in Binary Images by Sundus Ebraheem

“…In this paper, a new algorithm is proposed for circle detection, called Point Search Circle Detection (PSCD), which detects points and assumes them as inspection points on the circle circumference by using them to create a virtual circle to match it with the original image. …”
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Retracted: Image Target Detection Algorithm of Smart City Management Cases by Ping Tan, Kedun Mao, Sheng Zhou

“…The ultra-spectral target detection algorithm extracts some content indicators from the initial data, and finally realizes the optimization of the algorithm. …”
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RATIONAL DIAGNOSTIC METHODS AND ALGORITHMS FOR DETECTING KIDNEY DISEASES IN CHILDREN (ENGLISH) by A.E. Naushabaeva, K.A. Kabulbaev, A.L. Rumyantsev, V. Brocker, J. Ehrich

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Underwater object detection algorithm integrating image enhancement and deformable convolution by Lijia Guo, Xiangchun Liu, Dongsheng Ye, Xuebao He, Jianxin Xia, Wei Song

“…To address these limitations, this study proposes a novel underwater object detection algorithm, DeformableConvModule-You Only Look Once (DCM-YOLO), based on YOLOv8s. …”
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Advancements in detecting Deepfakes: AI algorithms and future prospects − a review by Laishram Hemanta Singh, Panem Charanarur, Naveen Kumar Chaudhary

“…Innovative AI techniques, such as deep learning, transfer learning, Long Short-Term Memory (LSTM) networks, and Convolutional Neural Networks (CNNs), have been developed to effectively detect and combat Deepfakes. Deep learning algorithms, specifically CNNs, which are inspired by the visual cortex of the human brain, have proven to be effective in detecting Deepfake images and videos. …”
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YOLO-DAFS: A Composite-Enhanced Underwater Object Detection Algorithm by Shengfu Luo, Chao Dong, Guixin Dong, Rongmin Chen, Bing Zheng, Ming Xiang, Peng Zhang, Zhanwei Li

“…However, underwater environments introduce challenges, such as poor lighting, high complexity, and diverse marine organism shapes, leading to missed detections or false positives in deep learning-based algorithms. …”
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YOLO deep learning algorithm for object detection in agriculture: a review by Kamalesh Kanna S, Kumaraperumal Ramalingam, Pazhanivelan P, Jagadeeswaran R, Prabu P.C.

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