Deformable Feature Fusion and Accurate Anchors Prediction for Lightweight SAR Ship Detector Based on Dynamic Hierarchical Model Pruning by Yue Guo, Shiqi Chen, Ronghui Zhan, Wei Wang, Jun Zhang

“…To address these challenges, this article proposes a novel SAR ship detection network called DFES-Net, which incorporates deformable feature fusion and accurate anchor prediction to enhance detection performance. …”
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A novel lightweight deep learning framework using enhanced pelican optimization for efficient cyberattack detection in the Internet of Things environments by Yaozhi Chen, Yan Guo, Yun Gao, Baozhong Liu

“…To counter these challenges, the current study proposes a hybrid model incorporating an efficient convolutional neural network (CNN) and an enhanced pelican optimization algorithm (EPOA) to detect IoT network attacks. Inspired by how pelicans hunt, EPOA maximizes CNN’s hyperparameters and feature selection for higher accuracy and efficiency in computation. …”
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Research on Leak Detection and Localization Algorithm for Oil and Gas Pipelines Using Wavelet Denoising Integrated with Long Short-Term Memory (LSTM)–Transformer Models by Yunbin Ma, Zuyue Shang, Jie Zheng, Yichen Zhang, Guangyuan Weng, Shu Zhao, Cheng Bi

“…This paper introduces a novel leakage detection and localization algorithm for oil and gas pipelines, integrating wavelet denoising with a Long Short-Term Memory (LSTM)-Transformer model. …”
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An Enhanced Bio-inspired GWO–DE Technique for Efficient Feature Selection in the EEG-RSVP Paradigm by S. Abinayaa, S. S. Sridhar

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Research on Abnormal Ship Brightness Temperature Detection Based on Infrared Image Edge-Enhanced Segmentation Network by Xiaobin Hong, Guanqiao Chen, Yuanming Chen, Ruimou Cai

“…In the Fusion Unit, edge features guide the extraction of infrared ship features in the backbone network, resulting in feature maps rich in edge information. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…By integrating original concentration data and residual features, gas anomalies are effectively identified by the proposed method, with the detection rate reaching a range of 93–96% and the false alarm rate controlled below 5%. …”
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Enhancing automated detection and classification of dementia in individuals with cognitive impairment using artificial intelligence techniques by Shoayee Dlaim Alotaibi, Abeer A. K. Alharbi

“…In addition, the wavelet neural network (WNN) classifier is employed to detect and classify dementia. Finally, the improved salp swarm algorithm (ISSA) is implemented to choose the WNN technique’s hyperparameters optimally. …”
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Detection of acute dengue virus infection, with and without concurrent malaria infection, in a cohort of febrile children in Kenya, 2014-2019, by clinicians or machine learning alg... by David M Vu, Amy R Krystosik, Bryson A Ndenga, Francis M Mutuku, Kelsey Ripp, Elizabeth Liu, Carren M Bosire, Claire Heath, Philip Chebii, Priscilla Watiri Maina, Zainab Jembe, Said Lipi Malumbo, Jael Sagina Amugongo, Charles Ronga, Victoria Okuta, Noah Mutai, Nzaro G Makenzi, Kennedy A Litunda, Dunstan Mukoko, Charles H King, A Desiree LaBeaud

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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
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A Novel Dangerous Goods Detection Network Based on Multi-Layer Attention Mechanism in X-Ray Baggage Images by Xu Yang, Ting Lan, Yili Xu

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Multisensor Diffusion-Driven Optical Image Translation for Large-Scale Applications by Joao Gabriel Vinholi, Marco Chini, Anis Amziane, Renato Machado, Danilo Silva, Patrick Matgen

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Back Propagation Neural Network model for analysis of hyperspectral images to predict apple firmness by Shuiping Li, Yueyue Chen, Xiaobo Zhang, Junbo Wang, Xuanxiang Gao, Yunhong Jiang, Zhaojun Ban, Cunkun Chen

“…This research provides a reference point for the non-destructive detection of apple in the selection of preprocessing, feature selection algorithms, and predicting firmness model.…”
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DMSA-Net: a deformable multiscale adaptive classroom behavior recognition network by Chunyu Dong, Jing Liu, Shenglong Xie

“…Moreover, there are occlusions and scale differences in the front and back rankings, which can easily cause confusion and interference with target features in the detection process, greatly limiting the accurate recognition ability of existing visual algorithms for classroom behavior. …”
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Domain Diversification Progressive Cross-Domain Weakly-Supervised Real-time Object Detection by LI Chengyan, ZHENG Qisen, WANG Hao

“…A real-time object detector matching the cross-domain framework is constructed based on SSD algorithm to realize real-time object detection under weakly supervised conditions. …”
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Fusion of non-iterative deep neural network feature extraction with kernel extreme learning machine for plant disease classification by Kirti Kirti, Navin Rajpal, Virendra P. Vishwakarma, Pramod Kumar Soni

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Football sports video tracking and detection technology based on YOLOv5 and DeepSORT by Bin Wang

“…The detection performance under target overlap and uneven lighting and shadows exceeded 90%, and the difference between the algorithm and other algorithms was at least greater than 2%. …”
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Methodology for detecting anomalies in cyber attack assessment data using Random Forest and Gradient Boosting in machine learning by A. S. Kechedzhiev, O. L. Tsvetkova, A. I. Dubrovina

“…The work done is the result of a comprehensive analysis of a machine learning model designed to detect cyberattacks. It includes several key steps and methods that allow us to evaluate the effectiveness of the model, identify important features, and analyze performance for various attacks.…”
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MACHINE LEARNING TECHNIQUES FOR RETINOPATHY DETECTION IN DIABETIC PATIENTS by Ajay Kushwaha, Ahankari Sachin Suresh, Chennoju Phanindra, Anil Kumar Sahu, Devanand Bhonsle, Yamini Chouhan

“…A range of techniques, from traditional clinical methods to advanced machine learning algorithms, are employed to detect retinopathies in diabetic patients. …”
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A Laser-Based SLAM Algorithm of the Unmanned Surface Vehicle for Accurate Localization and Mapping in an Inland Waterway Scenario by Yang Wang, Chao Liu, Jiahe Liu, Jinzhe Wang, Jianbin Liu, Kai Zheng, Rencheng Zheng

“…Subsequently, a generalized iterative closest point (GICP) algorithm incorporating rejection sampling is integrated to enhance the accuracy of point cloud matching, involving a two-phase filtering process to select key feature points for matching. …”
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Marine fish species recognition based on improved YOLOv5s by ZHANG Haifeng, LU Xinchun, FENG Bo, YANG Jin

“…Finally, optimized the path aggregation network of the model to enhance the feature fusion ability of the network.ResultsThe experimental results showed that the improved Our⁃YOLOv5s model had a mAP of 98.4% and a detection speed of 64 s-1 in the dataset, which was 2.4% and 6 s-1 higher than the original model, respectively.ConclusionThe model can meet the real⁃time detection requirements of marine fish.…”
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