Automated Fovea Detection in Spectral Domain Optical Coherence Tomography Scans of Exudative Macular Disease by Jing Wu, Sebastian M. Waldstein, Alessio Montuoro, Bianca S. Gerendas, Georg Langs, Ursula Schmidt-Erfurth

“…The fovea is classified into 3 main appearances to both specify the detection algorithm used and reduce computational complexity. …”
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An Effective Method for Detecting Cyber Attacks on Computer Networks from the NSL-KDD Data Set by Shaik Aseena Babu, Reddy Rajeswara, Vullam Nagagopi Raju, Reddy Gondi Konda, Shaik Subhani

“…Logistic regression models can fully favor network traffic structure information to capture features more comprehensively. Experimental outcomes show that the algorithm behaves better than traditional methods.…”
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Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9 by Amani A. Alsabei, Tahani M. Alsubait, Hosam H. Alhakami

“…This study introduces an innovative approach for detecting abnormal behavior in real-time during the Hajj pilgrimage, utilizing the advanced capabilities of the YOLOv9 algorithm. …”
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Comprehensive dataset for fault detection and diagnosis in inverter-driven permanent magnet synchronous motor systemszenodo by Abdelkabir Bacha, Ramzi El Idrissi, Khalid Janati Idrissi, Fatima Lmai

“…This work introduces a new, comprehensive dataset for Fault Detection and Diagnosis (FDD) in inverter-driven Permanent Magnet Synchronous Motor (PMSM) systems. …”
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An Attention-Enhanced 3D-CNN Framework for Spectrogram-Based EEG Analysis in Epilepsy Detection by Ziaullah Khan, Aakanksha Dayal, Hee-Cheol Kim

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Enhanced YOLO11 for lightweight and accurate drone-based maritime search and rescue object detection. by Beigeng Zhao, Jiawen Zhao, Rui Song, Lizhi Yu, Xia Zhang, Jiren Liu

“…These include integrating a Space-to-Depth module into the Backbone, incorporating a content-aware upsampling algorithm in the Neck, and adding an extra detection head to better exploit shallow image features. …”
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Research on concrete structure damage detection based on piezoelectric sensing technology and morphological fractal method by Hanqing Zhong, Liwei Shuai, Dongmin Deng

“…Abstract This study proposes a concrete piezoelectric sensing detection method based on mathematical morphology and fractal theory, which effectively monitors and quantitatively assesses the dynamic evolution process of damage cracks in concrete structures under impact loads. …”
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Graph-Regularized Orthogonal Non-Negative Matrix Factorization with Itakura–Saito (IS) Divergence for Fault Detection by Yabing Liu, Juncheng Wu, Jin Zhang, Man-Fai Leung

“…As an effective dimensionality reduction tool, NMF can decompose complex datasets into non-negative matrices with practical and physical significance, thereby extracting key features of the process. This paper presents a novel approach to fault detection in industrial processes, called Graph-Regularized Orthogonal Non-negative Matrix Factorization with Itakura–Saito Divergence (GONMF-IS). …”
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An optimized domain-specific shrimp detection architecture integrating conditional GAN and weighted ensemble learning by L. Ravi Kumar, Ravi Kumar Tata, T. R. Mahesh, Endris Mohammed Ali

“…The Enhanced Shrimp Detection algorithm generates the unique features set and also various parameters fetched from foundational classifiers. …”
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Wearable sensor-based fall detection for elderly care using ensemble machine learning techniques by Ch Gangadhar, P Pavithra Roy, R. Dinesh Kumar, Janjhyam Venkata Naga Ramesh, S. Ravikanth, N. Akhila

“…The suggested strategy outperformed modern fall identification techniques when tested using the labeled KFall database, achieving average precision of 95 percent, 96 percent, as well as 98 percent for Non-Falls, Pre-Falls, as well as detectable fall incidents, correspondingly. The whole assessment proved the algorithmic learning structure's efficacy. …”
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A novel and efficient personalized stress detection technique using a deep learning model by Ulligaddala Srinivasarao, Gopisetty Rathnamma, M. Satish Kumar, Lakshmipathi Anantha, Rakesh Kumar Donthi, T. Jhansi Rani

“…Several limitations occurred, such as higher training time, high time consumption, and limited features utilized to train the model. The proposed novelty of the technique is developed to overcome these issues and provide efficient stress detection. …”
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Spectral monitoring technology for gas concentrations of multiple target components in oil and gas leakage detection by Zhirong ZHANG, Pengchao CHEN, Yongjun CAI, Wenyou DU, Zhonglin LI, Yuntao PENG, Pengshuai SUN, Bian WU

“…ObjectiveTraditional gas monitoring methods for oil and gas leakage fall short in meeting the growing demands for the safe operation and maintenance of smart pipeline networks, due to factors such as low detection sensitivity levels, short calibration intervals, frequent false alarms, limited ranges of detectable gases, susceptibility to environmental interference, and reliance on charged sensors. …”
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Efficient wildlife monitoring: Deep learning-based detection and counting of green turtles in coastal areas by Naoya Noguchi, Hideaki Nishizawa, Taro Shimizu, Junichi Okuyama, Shohei Kobayashi, Kazuyuki Tokuda, Hideyuki Tanaka, Satomi Kondo

“…Then, the BoT-SORT object-tracking algorithm was implemented to track green turtles detected using the YOLOv7 model, and the counting of individuals was automated. …”
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A Low-Cost Antipodal Vivaldi Antenna-Based Peanut Defect Rate Detection System by Yuanyuan Yin, Fangyan Ma, Xiaohong Liu, Shuhao Wang, Junjie Xia, Liqing Zhao

“…Differing from traditional and often expensive or complex detection methods, our approach utilizes a low-cost antipodal Vivaldi antenna, complemented by a custom-designed defect rate detection system. …”
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Abnormal event detection based on local topology and l_1/2norm regularize by Qing YU, Ken CHEN, Meng LI, Fei LI

“…A new dictionary learning method was proposed by introducing a local topology term to describe structural information of video events and using the l_1/2norm as the sparsity constraint to the representation coefficients based on the traditional analysis dictionary learning method.In feature extraction,a histogram of interaction force(HOIF) containing rich motion information and a histogram of oriented gradient(HOG) containing texture information were merged.Then,the improved dictionary was used to train the feature data.Finally,the reconstruction error of the testing sample under the dictionary was used to determine whether the testing sample was an abnormal sample.Experiments on UMN show the high performance of the algorithm.Compared with the state-of-the-art algorithms,the analysis dictionary classification algorithm based on local topology and l_1/2norm has made more effective detection on the abnormal events in the crowd.…”
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TCBGY net for enhanced wear particle detection in ferrography using self attention and multi scale fusion by Lei He, Haijun Wei, Cunxun Sun

“…To address challenges such as false detection, missed detection of small wear particles, difficulty in distinguishing overlapping and similar abrasions, and handling complex image backgrounds, this paper proposes an algorithm called TCBGY-Net for detecting wear particles in ferrography images. …”
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Unveiling smart contract vulnerabilities: Toward profiling smart contract vulnerabilities using enhanced genetic algorithm and generating benchmark dataset by Sepideh HajiHosseinKhani, Arash Habibi Lashkari, Ali Mizani Oskui

“…This study introduces a novel approach to detecting, identifying, and profiling SC vulnerabilities, comprising two key components: an updated analyzer named SCsVulLyzer (V2.0) and an advanced Genetic Algorithm (GA) profiling method. …”
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Introducing HeliEns: A Novel Hybrid Ensemble Learning Algorithm for Early Diagnosis of <i>Helicobacter pylori</i> Infection by Sultan Noman Qasem

“…The development of HeliEns involved rigorous data preprocessing steps, including data cleaning, encoding of categorical variables, and feature scaling, to ensure the dataset’s suitability for quantum machine learning algorithms. …”
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AI may help to predict thyroid nodule malignancy based on radiomics features from [18F]FDG PET/CT by Krystian Ślusarz, Mikolaj Buchwald, Adrian Szczeszek, Szymon Kupinski, Anna Gramek-Jedwabna, Wojciech Andrzejewski, Juliusz Pukacki, Robert Pękal, Marek Ruchała, Rafał Czepczyński, Cezary Mazurek

“…Conclusions With an AI-based algorithm using radiomics features it is possible to detect the malignancy of thyroid nodule. …”
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Sql injection detection using Naïve Bayes classifier: A probabilistic approach for web application security by Lu Zhexi

“…This collection of attributes is employed to generate a feature vector that serves as the input for the Naive Bayes classification algorithms. …”
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