Indoor Multidimensional Reconstruction Based on Maximal Cliques by Yongtong Zhu, Lei Li, Na Liu, Qingdu Li, Ye Yuan

“…Applying deep learning models to obtain stereoscopic scene information, accompanied by algorithms such as target detection and semantic segmentation to obtain finer labels of things, is the dominant paradigm for robots. …”
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Artificial Intelligence Approach in Hip Prosthesis Identification and Addressing Radiographic Outcome Measures by Omar Musbahi, MSc, ChM, Savvas Hadjixenophontos, MEng, Saran S. Gill, Iris Soteriou, Bsc, Kyriacos Pouris, Bsc, Takuro Ueno, PhD, Justin P. Cobb, MCh

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Mapping Burned Forest Areas in Western Yunnan, China, Using Multi-Source Optical Imagery Integrated with Simple Non-Iterative Clustering Segmentation and Random Forest Algorithms i... by Yue Chen, Weili Kou, Wenna Miao, Xiong Yin, Jiayue Gao, Weiyu Zhuang

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High-Impedance Fault Detection in Electric Power Distribution Network Using Local Pattern Transformation Methods and Bidirectional Long Short–Term Memory by Rini Varghese P, M. S. P. Subathra, S. Thomas George, Geno Peter, Albert Alexander Stonier, Sairamya N, Ananthi A, Vivekananda Ganji

“…In the proposed algorithm, 1D signal analysis for HIF detection in the MV distribution system is performed for the first time for fault analysis. …”
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Multimodal framework for phishing attack detection and mitigation through behavior analysis using EM-BERT and SPCA-BASED EAI-SC-LSTM by Mahmoud Murhej, G. Nallasivan

“…Then, by utilizing Spherical Principal Component Analysis (SPCA), the features are extracted. Further, the optimal features are chosen by using the Cauchy distribution-based Seagull Optimization Algorithm (CSOA). …”
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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…The former can not only assess the confidence level of each pixel category but also make regional boundaries clearer, and the latter can replace the test set so that all samples can be used for change detection. The experimental results show that the OOB accuracy obtained by spatial features with whole block sampling was <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>7.2</mn><mo>%</mo></mrow></semantics></math></inline-formula> higher than that obtained by spectral features with pixel-based sampling and 2–3% higher than that for block center sampling, of which the highest value reached <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>98.8</mn><mo>%</mo></mrow></semantics></math></inline-formula>. …”
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A novel damage detection method based on sequential iteration and Gaussian mixture model for structural health monitoring under environmental effects by Jie-zhong Huang, Jian Yang, Dong-sheng Li, Wei-chen Kong, Ya-fei Wang

“…Abstract Environmental effects often cause variability in dynamic features, obscuring actual damage indicators and leading to false alarms in damage detection. …”
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Advanced machine learning techniques reveal multidimensional EEG abnormalities in children with ADHD: a framework for automatic diagnosis by Ying Mao, Ying Mao, Xuchen Qi, Xuchen Qi, Xuchen Qi, Lingyan He, Shan Wang, Zhaowei Wang, Fang Wang, Fang Wang

“…Then, four widely-employed machine learning algorithms (including random forest (RF), XGBoost, CatBoost, and LightGBM) were used for classification calculations, and the SHAP algorithm was then used to assess the importance of the contributing features to interpret the model’s decision process.ResultsThe results showed that the highest classification accuracy of 99.58% for pediatric ADHD detection was obtained with the CatBoost model based on the optimal feature subset of 206 features (PSD/FuzEn/MI = 53/5/148). …”
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Early detection of thermal image based T1 breast cancer using enhanced multiwavelet denoised convolution neural network with region based analysis by P. Geetha, S. UmaMaheswari

“…Amplified cancer cell images are analyzed using the proposed Multiwavelet-Deep Denoised Convolutional Neural Network (MWTDnCNN) algorithm for T1 cancer cell detection. Amplified T1 stage cancer cell has higher thermal conductivity (k) and heat capacity (Cp), which helps to detect T1 cancer cell tissue due to the enhanced pixel feature. …”
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Unmasking social bots: how confident are we? by James Giroux, Gangani Ariyarathne, Alexander C. Nwala, Cristiano Fanelli

“…Despite the progress made in developing multiple sophisticated social bot detection algorithms and tools, bot detection remains a challenging, unsolved problem that is fraught with uncertainty due to the heterogeneity of bot behaviors, training data, and detection algorithms. …”
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Blockchain covert communication scheme based on the cover of normal transactions by Pengkun JIANG, Wenyin ZHANG, Jiuru WANG, Shanyun HUANG, Wanshui SONG

“…With the development of computer technology, the situation of modern network attack and defense is becoming increasingly severe, and the problem of secure transmission of secret information needs to be solved urgently.Covert communication technology embeds secret information into the carrier and transmits the information safely through the covert channel.However, the traditional covert channels face the challenges of data damaging, attack, detection and so on, which cannot meet the higher security requirements.As a public data platform, blockchain can embed secret information under the cover of a large number of transactions.With its tamper proof, anonymity, decentralization and other characteristics, blockchain can well solve the problems of traditional covert channels and achieve secure covert communication.However, the existing blockchain covert communication schemes are limited by low communication efficiency and poor security.How to improve safety and efficiency of covert communication is a research focus of blockchain covert communication.Motivated by this issue, a blockchain covert communication scheme based on the cover of normal transactions was proposed.The hash algorithm was used to build a transmission-free password table to embed secret information without changing any transaction data.Using the elliptic curve feature, transactions with hidden information can be quickly screened out from a large number of transactions, to extract secret information quickly.This scheme improves the security and efficiency of covert communication and has strong portability.Theoretical analysis shows that attackers cannot distinguish between ordinary transactions and special transactions.This scheme has high anti-detection and scalability.Besides, the experimental results of the bitcoin test network show the high efficiency of this scheme.…”
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Cucumber Leaf Segmentation Based on Bilayer Convolutional Network by Tingting Qian, Yangxin Liu, Shenglian Lu, Linyi Li, Xiuguo Zheng, Qingqing Ju, Yiyang Li, Chun Xie, Guo Li

“…The major contributions of this study are as follows: (1) Utilized Fully Convolutional Object Detection (FCOS) for plant leaf detection, incorporating ResNet-50 with the Convolutional Block Attention Module (CBAM) and Feature Pyramid Network (FPN) to enhance Region of Interest (RoI) feature extraction from canopy top-view images. (2) Extracted the sub-region of the RoI based on the position of the detection box, using this region as input for the BCNet, ensuring precise segmentation. (3) Utilized instance segmentation of canopy top-view images using BCNet, improving segmentation accuracy. (4) Applied the Varifocal Loss Function to improve the classification loss function in FCOS, leading to better performance metrics. …”
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Radiomics for Machine Learning—A Multi-Class System for the Automatic Detection of COVID-19 and Community-Acquired Pneumonia from Computed Tomography Images by Vasileia Paschaloudi, Dimitris Fotopoulos, Ioanna Chouvarda

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A Dynamic Measurement System Based on Adaptive Clustering and Multi-Classifier by Bowen Shi, Hongjian You, Huixian Wang

“…It employs a decision function to optimize the localization region across various classifier detection and tracking algorithms for targets. Additionally, a state judgment module scores the classifiers based on target state and depth information, which allows for adaptive selection of the classifier. …”
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Research on Detection of Icing Cover Transmission Lines Under Different Weather Conditions Based on Wide-Field Dynamic Convolutional Network LDKA-NET by Xinsheng Dong, Yuanhao Wan, Yongcan Zhu, Chao Ji

“…To address the issue of low detection accuracy for icing transmission line defects with existing models, this paper proposes a defect detection algorithm for icing transmission line defects under different weather conditions based on a Large Dynamic Kernel Aggregation Net (LDKA-NET). …”
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Accurate recognition of UAVs on multi-scenario perception with YOLOv9-CAG by Jincan Zhu, Jian Rong, Weili Kou, Qingyang Zhou, Peichun Suo

“…This algorithm integrates the detection capabilities of visible light, infrared, and audio signals. …”
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Identification of Spambots and Fake Followers on Social Network via Interpretable AI-Based Machine Learning by Danish Javed, Noor Zaman Zaman, Navid Ali Khan, Sayan Kumar Ray, Arafat Al-Dhaqm, Victor R. Kebande

“…Furthermore, we analyze several features and provide a unique feature set that is optimized to offer excellent performance for bot detection. …”
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Bridging the Gap Between Computational Efficiency and Segmentation Fidelity in Object-Based Image Analysis by Fernanda Pereira Leite Aguiar, Irenilza de Alencar Nääs, Marcelo Tsuguio Okano

“…A critical issue in image analysis for analyzing animal behavior is accurate object detection and tracking in dynamic and complex environments. …”
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Minima-YOLO: A Lightweight Identification Method for Lithium Mineral Components Under a Microscope Based on YOLOv8 by Zeyang Qiu, Xueyu Huang, Xiangyu Xu

“…A series of comparative experiments confirmed its superior performance over other advanced object detection algorithms. This algorithm, with its highly efficient lightweight design and rapid inference speed, provides an intelligent, efficient, and eco-friendly computer vision method for the rapid sorting of lithium mineral components.…”
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Establishment and Application of Wireless Fingerprint Library for Urban Rail Transit Vehicle-wayside Communication by WU Jie

“…The library utilizes the DeepFS algorithm, enabling adaptive updates of the wireless feature data for each grid. …”
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