Improving Electricity Theft Detection using Combination of Improved Crow Search Algorithm and Support Vector Machine by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

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YOLO-LSM: A Lightweight UAV Target Detection Algorithm Based on Shallow and Multiscale Information Learning by Chenxing Wu, Changlong Cai, Feng Xiao, Jiahao Wang, Yulin Guo, Longhui Ma

“…To address challenges such as large-scale variations, high density of small targets, and the large number of parameters in deep learning-based target detection models, which limit their deployment on UAV platforms with fixed performance and limited computational resources, a lightweight UAV target detection algorithm, YOLO-LSM, is proposed. …”
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Comparison of Deep Learning Models and Optimization Algorithms in the Detection of Scoliosis and Spondylolisthesis from X-Ray Images by Abdullah Erhan Akkaya, Cengiz Hark, Harun Güneş

“…This study aims to classify spine X-ray images according to three possible conditions (Normal, Scoliosis, and Spondylolisthesis) and to exploit the potential of these X-ray images to detect possible diseases occurring in the spine. The performance of deep learning models and optimization algorithms used in this process was evaluated. …”
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ContourTL-Net: Contour-Based Transfer Learning Algorithm for Early-Stage Brain Tumor Detection by N. I. Md. Ashafuddula, Rafiqul Islam

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Improved fish swarm algorithm based on chaos and its application in abnormal detection of industrial control network by Yaping WU, Hongzhao DONG, Yingying LIN, Jing LIU

“…Artificial fish swarm algorithm as a new type of bionic swarm intelligence optimization algorithm has been successfully used in a variety of optimization problems and practical engineering field,but when faced with the complex optimization problems,especially the multiple extreme value of peak and multimodal function optimization problems,due to the objective function has many local minima,inevitably there are defects such as premature and slow convergence speed.The random and ergodic theory was introduced into the basic artificial fish swarm algorithm,and an improved algorithm was constructed to make artificial fish swarm search avoid possible local extremum.The effectiveness of the algorithm was validated in the simulation application in industrial control network anomaly detection.Compared with the basic artificial fish school algorithm,the chaos improved artificial fish swarm algorithm can effectively avoid the long-term search of the algorithm near the local extreme value.The algorithm has better performance in terms of global convergence and the search efficiency is more prominent.…”
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Implementation of Blockchain Technology for Image Plagiarism Detection Using DCT, AES128, and SHA-1 Algorithms by Filbert Duran, Leonardo, Shickhem, Yennimar

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Detection of Drivers Drowsiness on Four-Wheeled Vehicles using the Haar Cascade Algorithm and Eye Aspect Ratio by Maukar Maukar

“…This study implements the use of the Haar Cascade Classifier algorithm in detecting the drowsiness of four-wheeled vehicle drivers and the Eye Aspect Ratio of the points that form the eyes using Euclidean Distance. …”
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Coherent Detection of Non-Orthogonal Spectrally Efficient Multicarrier Signals Using a Decision Feedback Algorithm by S. B. Makarov, S. V. Zavjalov, D. C. Nguyen, A. S. Ovsyannikova

“…At the same time, the efficiency of the detection algorithm with decision feedback turns out to be significantly lower than that when using the detection algorithm MLSE.Conclusion. …”
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Learning Gaussian Bayesian Network from Censored Data Subject to Limit of Detection by the Structural EM Algorithm by Ping-Feng Xu, Shanyi Lin, Qian-Zhen Zheng, Man-Lai Tang

“…In this paper, we introduce the censored Gaussian Bayesian network (GBN), an extension of GBNs designed to handle left- and right-censored data caused by instrumental detection limits. We further propose the censored Structural Expectation-Maximization (cSEM) algorithm, an iterative score-and-search framework that integrates Monte Carlo sampling in the E-step for efficient expectation computation and employs the iterative Markov chain Monte Carlo (MCMC) algorithm in the M-step to refine the network structure and parameters. …”
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Synergizing advanced algorithm of explainable artificial intelligence with hybrid model for enhanced brain tumor detection in healthcare by Kamini Lamba, Shalli Rani, Mohammad Shabaz

“…Abstract Brain tumor causes life-threatening consequences due to which its timely detection and accurate classification are critical for determining appropriate treatment plans while focusing on the improved patient outcomes. …”
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A Lightweight Remote-Sensing Image-Change Detection Algorithm Based on Asymmetric Convolution and Attention Coupling by Enze Zhang, Yan Li, Haifeng Lin, Min Xia

“…In recent years, breakthroughs in satellite sensor technology have generated vast volumes of data and complex scenes, presenting significant challenges for change-detection algorithms. Traditional methods rely on handcrafted features, which struggle to address the impacts of multi-source data heterogeneity and imaging condition differences. …”
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Development of a deep learning algorithm for radiographic detection of syndesmotic instability in ankle fractures with intraoperative validation by Joshua Kubach, Tobias Pogarell, Michael Uder, Mario Perl, Marcel Betsch, Mario Pasurka, Stefan Söllner, Rafael Heiss

“…The integration of an explainable deep-learning algorithm, trained on an intraoperative gold standard showed a 0.84 sensitivity for syndesmotic stability testing. …”
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GCS-YOLO: A Lightweight Detection Algorithm for Grape Leaf Diseases Based on Improved YOLOv8 by Qiang Hu, Yunhua Zhang

“…In view of the issues of high complexity, significant computational resource consumption, and slow inference speed in the detection algorithm for grape leaf diseases, this paper proposes GCS-YOLO, a lightweight detection algorithm based on an improved YOLOv8. …”
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Automatic detection of teacher behavior in classroom videos using AlphaPose and Faster R-CNN algorithms by Jing Huang, Harwati Hashim, Helmi Norman, Mohammad Hafiz Zaini, Xiaojun Zhang

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A Novel Dataset and Detection Method for Unmanned Aerial Vehicles Using an Improved YOLOv9 Algorithm by Depeng Gao, Jianlin Tang, Hongqi Li, Bingshu Wang, Jianlin Qiu, Shuxi Chen, Xiangxiang Mei

“…The comparison of experimental results shows that the developed method has better anti-interference performance than other algorithms. The detection method and dataset used to test the anti-interference capabilities in this study are expected to assist in the development and validation of related research methods.…”
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Deep learning with leagues championship algorithm based intrusion detection on cybersecurity driven industrial IoT systems by Saud S. Alotaibi, Turki Ali Alghamdi

“…This study presents a League Championship Algorithm Feature Selection with Optimal Deep Learning based Cyberattack Detection (CLAFS-ODLCD) technique for securing the digital ecosystem. …”
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Deep Learning Algorithm for Keratoconus Detection from Tomographic Maps and Corneal Biomechanics: A Diagnostic Study by Wiyada Quanchareonsap, Ngamjit Kasetsuwan, Usanee Reinprayoon, Yonrawee Piyacomn, Thitima Wungcharoen, Monthira Jermjutitham

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GC-Faster RCNN: The Object Detection Algorithm for Agricultural Pests Based on Improved Hybrid Attention Mechanism by Bolun Guan, Yaqian Wu, Jingbo Zhu, Juanjuan Kong, Wei Dong

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Impact of a deep-learning image reconstruction algorithm on image quality and detection of solid lung lesions by Joël Greffier, Maxime Pastor, Quentin Durand, Renaud Sales, Chris Serrand, Jean-Paul Beregi, Djamel Dabli, Julien Frandon

“…Purpose: To compare the impact of a deep-learning image reconstruction algorithm (Precise Image) with an iterative reconstruction algorithm on image quality and detection of solid lung lesions in chest CT images. …”
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Improved cancer detection through feature selection using the binary Al Biruni Earth radius algorithm by El-Sayed M. El-Kenawy, Nima Khodadadi, Marwa M. Eid, Ehsaneh Khodadadi, Ehsan Khodadadi, Doaa Sami Khafaga, Amel Ali Alhussan, Abdelhameed Ibrahim, Mohamed Saber

“…In this study, a binary version of the Advanced Al-Biruni Earth Radius (bABER) algorithm is proposed for the intelligent removal of unnecessary data and identifying the most essential features for cancer detection. …”
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