Abnormality detection and privacy protection strategies for power marketing inspection business of cyber–physical–social systems using big data and artificial intelligence by Li Kai, Mo Pingyan, Yang Yongjiao, Xie Hanyang, Shen Zhixiong

“…The proposed model incorporates a work order correlation matching algorithm, a fault interval detection algorithm, an electricity consumption prediction algorithm, and a business anomaly identification algorithm. …”
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Detection of the stem-boring damage by pine shoot beetle (Tomicus spp.) to Yunan pine (Pinus yunnanensis Franch.) using UAV hyperspectral data by Meng-Ying Liu, Guang-Yun Li, Lei Shi, Ya-Ying Li, Huai Liu

“…However, there is a lack of studies investigating the application and accuracy of UAV hyperspectral data for detecting PSB stem-boring damage.MethodsIn this study, we compared the differences in spectral features of healthy pines (H level), three levels of shoot-feeding damage (E, M and S levels), and the stem-boring damage (T level), and then used the Random Forest (RF) algorithm for detecting stem-boring damage by PSB.ResultsThe specific canopy spectral features, including red edge (such as Dr, SDr, and D711), blue edge (such as Db and SDb), and chlorophyll-related spectral indices (e.g., MCARI) were sensitive to PSB stem-boring damage. …”
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Detection of Parabolic Antennas in Satellite Inverse Synthetic Aperture Radar Images Using Component Prior and Improved-YOLOv8 Network in Terahertz Regime by Liuxiao Yang, Hongqiang Wang, Yang Zeng, Wei Liu, Ruijun Wang, Bin Deng

“…In order to tackle the challenges associated with component identification in satellite ISAR imagery, this study employs the Improved-YOLOv8 model, which was developed by incorporating the YOLOv8 algorithm, an adaptive detection head known as the Dynamic head (Dyhead) that utilizes an attention mechanism, and a regression box loss function called Wise Intersection over Union (WIoU), which addresses the issue of varying sample difficulty. …”
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Securing IoT devices with zero day intrusion detection system using binary snake optimization and attention based bidirectional gated recurrent classifier by Ali Saeed Almuflih, Ilyos Abdullayev, Sergey Bakhvalov, Rustem Shichiyakh, Bibhuti Bhusan Dash, K. B. V. Brahma Rao, Kritika Bansal

“…This manuscript presents a Binary Snake Optimizer with DL-Enabled Zero-Day Attack Detection and Classification (BSODL-ZDADC) method. …”
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ParaU-Net: An improved UNet parallel coding network for lung nodule segmentation by Yingqi Lu, Xiangsuo Fan, Jinfeng Wang, Shaojun Chen, Jie Meng

“…Accurate segmentation of lung nodules is crucial for the early detection of lung cancer and other pulmonary diseases. …”
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CBLN-YOLO: An Improved YOLO11n-Seg Network for Cotton Topping in Fields by Yufei Xie, Liping Chen

“…The positioning of the top bud by the topping machine in the cotton topping operation depends on the recognition algorithm. The detection results of the traditional target detection algorithm contain a lot of useless information, which is not conducive to the positioning of the top bud. …”
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Research progress of digital image forensic techniques based on deep learning by Tong QIAO, Hongwei YAO, Binmin PAN, Ming XU, Yanli CHEN

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Conv1D-LSTM: Autonomous Breast Cancer Detection Using a One-Dimensional Convolutional Neural Network With Long Short-Term Memory by Mitanshi Rastogi, Meenu Vijarania, Neha Goel, Akshat Agrawal, Cresantus N. Biamba, Celestine Iwendi

“…To detect and classify breast cancer, the 1D CNN and LSTM are used to automatically extract and analyze features from distinguishing features from a real dataset generated from mammography reports. …”
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Machine learning for Internet of Things (IoT) device identification: a comparative study by Hamid Tahaei, Anqi Liu, Hamid Forooghikian, Mehdi Gheisari, Faiz Zaki, Nor Badrul Anuar, Zhaoxi Fang, Longjun Huang

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Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation paramet... by Xin-Yue Song, Xin-Peng Xie, Wen-Jing Xu, Yu-Jia Cao, Bin-Miao Liang

“…Abstract Background The integration of machine learning (ML) algorithms enables the detection of diffusion abnormalities-related respiratory changes in individuals with normal body mass index (BMI), overweight, and obesity based on BMI and pulmonary ventilation parameters. …”
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ReliefSeq: a gene-wise adaptive-K nearest-neighbor feature selection tool for finding gene-gene interactions and main effects in mRNA-Seq gene expression data. by Brett A McKinney, Bill C White, Diane E Grill, Peter W Li, Richard B Kennedy, Gregory A Poland, Ann L Oberg

“…For gene-gene interactions, gwak-Relief-F outperforms all comparison methods at ranking relevant genes in all but the highest fold change/highest signal situations where it performs similarly. The gwak-Relief-F algorithm outperforms Random Forests for detecting relevant genes in all simulation experiments. …”
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Blind audio watermarking mechanism based on variational Bayesian learning by Xin TANG, Zhao-feng MA, Xin-xin NIU, Yi-xian YANG

“…In order to improve the performance of audio watermarking detection,a blind audio watermarking mechanism using the statistical characteristics based on MFCC features of audio frames was proposed.The spread spectrum watermarking was embedded in the DCT coefficients of audio frames.MFCC features extracted from watermarked audio frames as well as un-watermarked ones were trained to establish their Gaussian mixture models and to estimate the parameters by vatiational Bayesian learning method respectively.The watermarking was detected according to the maximum likelihood principle.The experimental results show that our method can lower the false detection rate compared with the method using EM algorithm when the audio signal was under noise and malicious attacks.Also,the experiments show that the proposed method achieves better performance in handling insufficient training data as well as getting rid of over-fitting problem.…”
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Algoritma Random Forest dan Synthetic Minority Oversampling Technique (SMOTE) untuk Deteksi Diabetes by Nurussakinah Nurussakinah, Muhammad Faisal, Irwan Budi Santoso

“…This research uses the Random Forest algorithm for diabetes detection. The purpose of the study is to detect diabetes with the Random Forest algorithm that provides accurate and efficient results in the early diagnosis of diabetic patients. …”
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Ship Contour Extraction from Polarimetric SAR Images Based on Polarization Modulation by Guoqing Wu, Shengbin Luo Wang, Yibin Liu, Ping Wang, Yongzhen Li

“…Finally, the ship’s contour is extracted from the optimized image using an edge-detection operator and an adaptive edge extraction algorithm. …”
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Method for quality assessment of image mosaic by Guo-ting WAN, Jun-ping WANG, Jin LI, Hong-hua CAO, Song WANG, Le WANG, IYA-ning L, Rong WEI

“…On the basis of the theory of existing methods for image quality assessment,a novel method for quality assessment of mosaicked image based on the information of image edge was presented.The method was in accordance with the features of mosaicked image.Firstly,the edges of image were detected.Then according to the information of image edges,the information of pixel error and structure was considered.The mean value and variance of the difference of edge map were related with the misplacement and the brightness mutation,which influenced the quality of mosaicked image.Lastly,the evaluate procedure was done based on the relationship.The new method was more consistent with the subjective feeling to the mosaicked image quality.This method accurately reflects the real quality of mosaicked image and the performance of the algorithm of image mosaic.…”
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Method for quality assessment of image mosaic by Guo-ting WAN, Jun-ping WANG, Jin LI, Hong-hua CAO, Song WANG, Le WANG, IYA-ning L, Rong WEI

“…On the basis of the theory of existing methods for image quality assessment,a novel method for quality assessment of mosaicked image based on the information of image edge was presented.The method was in accordance with the features of mosaicked image.Firstly,the edges of image were detected.Then according to the information of image edges,the information of pixel error and structure was considered.The mean value and variance of the difference of edge map were related with the misplacement and the brightness mutation,which influenced the quality of mosaicked image.Lastly,the evaluate procedure was done based on the relationship.The new method was more consistent with the subjective feeling to the mosaicked image quality.This method accurately reflects the real quality of mosaicked image and the performance of the algorithm of image mosaic.…”
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Mining behavior pattern of mobile malware with convolutional neural network by Xin ZHANG, Weizhong QIANG, Yueming WU, Deqing ZOU, Hai JIN

“…The features extracted by existing malicious Android application detection methods are redundant and too abstract to reflect the behavior patterns of malicious applications in high-level semantics.In order to solve this problem,an interpretable detection method was proposed.Suspicious system call combinations clustering by social network analysis was converted to a single channel image.Convolution neural network was applied to classify Android application.The model trained was used to find the most suspicious system call combinations by convolution layer gradient weight classification activation mapping algorithm,thus mining and understanding malicious application behavior.The experimental results show that the method can correctly discover the behavior patterns of malicious applications on the basis of efficient detection.…”
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Research on mulberry leaf disease recognition method based on deep learning by Ye Hui, Xiang Donghui, Zeng Songwei

“…The algorithm introduces a deformable convolution module within the Backbone to capture disease details and shapes more flexibly. …”
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Optimizing an image analysis protocol for ocean particles in focused shadowgraph imaging systems by Huanqing Huang, Alexander B. Bochdansky

“…To improve reconstruction of particles captured by Focused Shadowgraph Imaging (FoSI)—a system that excels at visualizing low-optical-density objects, we developed a novel object detection algorithm to process images with a resolution of ~ 12 μm per pixel. …”
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Historical Blurry Video-Based Face Recognition by Lujun Zhai, Suxia Cui, Yonghui Wang, Song Wang, Jun Zhou, Greg Wilsbacher

“…Historical motion picture films often have poorer resolution than modern digital imagery, making face detection a more challenging task. To approach this problem, we first propose a trunk–branch concatenated multi-task cascaded convolutional neural network (TB-MTCNN), which efficiently extracts facial features from blurry historical films by combining the trunk with branch networks and employing various sizes of kernels to enrich the multi-scale receptive field. …”
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