Deep encoder-decoder networks for belt longitudinal tear detection by Lei You, Minghua Luo, Xinglin Zhu, Bin Zhou

“…The input images are downscaled using a sorting algorithm to extract the information of pixels with high grayscale values as the input feature map for the neural network. …”
Get full text

An optimal federated learning-based intrusion detection for IoT environment by A. Karunamurthy, K. Vijayan, Pravin R. Kshirsagar, Kuan Tak Tan

“…The Chimp optimization algorithm is used in the proposed work to select optimal features. …”
Get full text

Knowledge Distillation in Object Detection for Resource-Constrained Edge Computing by Arief Setyanto, Theopilus Bayu Sasongko, Muhammad Ainul Fikri, Dhani Ariatmanto, I. Made Artha Agastya, Rakandhiya Daanii Rachmanto, Affan Ardana, In Kee Kim

“…We compare various KD algorithms to identify the technique that produces a smaller model with the modest accuracy drop. …”
Get full text

YOLO-WAD for Small-Defect Detection Boost in Photovoltaic Modules by Yin Wang, Wang Yun, Gang Xie, Zhicheng Zhao

“…Subsequently, an additional detection layer is added to the neck, and C2f is replaced by C2f-EMA (CSP bottleneck with two convolutions–efficient multi-scale attention mechanism), which can redistribute feature weights and prioritize relevant features and spatial details across image channels to improve feature extraction. …”
Get full text

River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection. This model incorporates the High-level Screening-feature Path Aggregation Network (HS-PAN), which refines feature fusion through a novel bottom-up fusion path, significantly enhancing its expressive power. …”
Get full text

Optimization of Random Forest Algorithm with Backward Elimination Method in Classification of Academic Stress Levels by Salsabila Dani Amalia, Mula Agung Barata, Pelangi Eka Yuwita

“…Data mining is often used to detect diseases, one of which is the Random Forest algorithm. …”
Get full text

Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…However, the performance of previous automated approaches has often been hindered by suboptimal feature selection and algorithms’ “black-box” nature, which adversely affect their interpretability and clinical applicability. …”
Get full text

Identification method for wheel/rail tread defects based on integrated partial convolutional network by CHENG Xiang, HE Jing, ZHANG Changfan, JIA Lin

“…Given the difficulties associated with accurately detecting minor wheelset damages, an enhanced adaptive spatial feature fusion (E-ASFF) detection approach was introduced. …”
Get full text

Novel topic detection method for microblog based on SVM filtration by Jun-xia CHENG, Zhi-tang LI, Ming-guang ZOU, Jin XIAO

“…A detection method based on SVM filtration was proposed.The method uses text feature as imported vectors to filtrate microblog news,reducing the amount of calculation greatly.A single-pass clustering algorithm based on the improvement of high-frequency words sorting was proposed,which can detect isolated points commendably.Experimental results show that the method can detect news topics from massive microblog data efficiently.…”
Get full text

Machine Learning-Based Approach for HIV/AIDS Prediction: Feature Selection and Data Balancing Strategy by Abdul Mizwar A Rahim, Ahmad Ridwan, Bambang Pilu Hartato, Firman Asharudin

“…HIV/AIDS remains a significant global health challenge, requiring accurate predictive models for early detection and improved clinical decision-making. However, developing an effective predictive model faces challenges such as data imbalance and the presence of irrelevant features, which can compromise model accuracy. …”
Get full text

Apple leaf disease severity grading based on deep learning and the DRL-Watershed algorithm by Zhifang Bi, Fumin Ma, Jiaxiong Guan, Jie Wu, Juxia Li, Fuzhong Li, Yanwen Li, Zhanli Liu

“…To address this issue, we propose a method for assessing the severity of apple leaf diseases based on a combination of improved HRNet and DRL-watershed algorithms. First, we selected HRNet_w32 as the backbone feature extraction network and incorporated a Normalization Attention Mechanism (NAM). …”
Get full text

Design of Jitter Compensation Algorithm for Robot Vision Based on Optical Flow and Kalman Filter by B. R. Wang, Y. L. Jin, D. L. Shao, Y. Xu

Get full text

Fractals and Independent Component Analysis for Defect Detection in Bridge Decks by Ikhlas Abdel-Qader, Fadi Abu-Amara, Osama Abudayyeh

“…Using Ground-Penetrating Radar (GPR) raw scans, this framework is composed of a feature extraction algorithm using fractals to detect defective regions and a deconvolution algorithm using banded-independent component analysis (ICA) to reduce overlapping between reflections and to estimate the radar waves travel time and depth of defects. …”
Get full text

An Automated Feature-Based Image Registration Strategy for Tool Condition Monitoring in CNC Machine Applications by Eden Lazar, Kristin S. Bennett, Andres Hurtado Carreon, Stephen C. Veldhuis

“…In this study, an MV system is developed alongside an automated, feature-based image registration strategy to spatially align tool wear images, enabling a more consistent and accurate detection of tool edge position. …”
Get full text

Early Detection of Parkinson's Disease: Ensemble Learning for Improved Diagnosis by Raut Komal, Balpande Vijaya

“…This paper proposed several machine learning algorithms such as Decision Tree, Random Forest, Logistic Regression and Support Vector Machine and design an ensemble of these models to detect and classify Parkinson's disease. …”
Get full text

Fast Modelling Algorithm for Realistic Three-Dimensional Human Face for Film and Television Animation by Limin Xu

“…Aiming at the face photos of film and television animation, this paper proposes a new fast three-dimensional (3D) face modelling algorithm. First of all, based on the LBF algorithm, this paper proposes a multifeature selection idea to automatically detect multiple features of the face. …”
Get full text

Code vulnerability detection method based on graph neural network by Hao CHEN, Ping YI

“…The schemes of using neural networks for vulnerability detection are mostly based on traditional natural language processing ideas, processing the code as array samples and ignoring the structural features in the code, which may omit possible vulnerabilities.A code vulnerability detection method based on graph neural network was proposed, which realized function-level code vulnerability detection through the control flow graph feature of the intermediate language.Firstly, the source code was compiled into an intermediate representation, and then the control flow graph containing structural information was extracted.At the same time, the word vector embedding algorithm was used to initialize the vector of basic block to extract the code semantic information.Then both of above were spliced to generate the graph structure sample data.The multilayer graph neural network model was trained and tested on graph structure data features.The open source vulnerability sample data set was used to generate test data to evaluate the method proposed.The results show that the method effectively improves the vulnerability detection ability.…”
Get full text

Adversarial training driven malicious code detection enhancement method by Yanhua LIU, Jiaqi LI, Zhengui OU, Xiaoling GAO, Ximeng LIU, Weizhi MENG, Baoxu LIU

“…To solve the deficiency of the malicious code detector’s ability to detect adversarial input, an adversarial training driven malicious code detection enhancement method was proposed.Firstly, the applications were preprocessed by a decompiler tool to extract API call features and map them into binary feature vectors.Secondly, the Wasserstein generative adversarial network was introduced to build a benign sample library to provide a richer combination of perturbations for malicious sample evasion detectors.Then, a perturbation reduction algorithm based on logarithmic backtracking was proposed.The benign samples were added to the malicious code in the form of perturbations, and the added benign perturbations were culled dichotomously to reduce the number of perturbations with fewer queries.Finally, the adversarial malicious code samples were marked as malicious and the detector was retrained to improve its accuracy and robustness of the detector.The experimental results show that the generated malicious code adversarial samples can evade the detector well.Additionally, the adversarial training increases the target detector’s accuracy and robustness.…”
Get full text

Research on malicious code variants detection based on texture fingerprint by Xiao-guang HAN, UWu Q, AOXuan-xia Y, UOChang-you G, Fang ZHOU

“…A texture-fingerprint-based approach is proposed to extract or detect the feature from malware content. The texture fingerprint of a malware is the set of texture fingerprints for each uncompressed gray-scale image block. …”
Get full text

ECG Paper Digitization and R Peaks Detection Using FFT by Ibraheam Fathail, Vaishali D. Bhagile

“…One of the most essential tools for detecting heart problems is the electrocardiogram (ECG). …”
Get full text