On the Problem of Radar Monitoring of Ice Cover Formation and Destruction on Inland Waters: First Assessments by Karaev Vladimir, Sorokin Eugeny, Panfilova Mariya Andreevna, Titchenko Yuriy, Meshkov Evgeniy Mihaylovich, Kovaldov Dmitry

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The analysis of fraud detection in financial market under machine learning by Jing Jin, Yongqing Zhang

“…Traditional fraud detection methods based on rules and statistical analysis are difficult to deal with increasingly complex and evolving fraud methods, and there are problems such as poor adaptability and high false alarm rate. …”
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Target Tracking Algorithm Based on Adaptive Scale Detection Learning by Dawei Yang

“…In this paper, to better solve the problem of low tracking accuracy caused by the sudden change of target scale, we design and propose an adaptive scale mutation tracking algorithm using a deep learning network to detect the target first and then track it using the kernel correlation filtering method and verify the effectiveness of the model through experiments. …”
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Machine Learning Techniques for Enhanced Intrusion Detection in IoT Security by Hanadi Hakami, Muhammad Faheem, Majid Bashir Ahmad

“…Therefore, it is necessary to find an efficient method for solving the problem by using classification with an intrusion detection system which analyzes enormous amounts of traffic data. …”
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Two-stage Detection Method for Abnormal Cluster Cervical Cells by LIANG Yi-qin, ZHAO Si-qi, WANG Hai-tao, HE Yong-jun

“…Cells adhere to each other, complex and diverse, which brings challenges to abnormal cell detection. To solve this problem, we proposed a two-stage detection method for cluster cervical abnormal cells. …”
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RESEARCH ON VISUAL DETECTION METHOD OF SOUND FILM BROKEN GLUE DEFECT by Jianchun Liu, Xunjin Jiang, Chaoqi Huang, Yuquan Lin

“… Broken glue defect is a common defect in sound film dispensing. Aiming at the problem of fuzzy glue region boundary frequently occurring in the detection process, an improved iterative maximum interclass variance method was proposed to detect broken glue defects. …”
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Underground helmet detection algorithm based on improved YOLOv8s by Jiaru YANG, Yinan QIN, Tianxu LI, Han ZHUANG

“…In order to solve the above problems, this study proposes a detection algorithm for underground safety helmets based on improved YOLOv8s, which is called PBSS-YOLOv8. …”
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AI bot to detect fake COVID‐19 vaccine certificate by Muhammad Arif, Shermin Shamsudheen, F Ajesh, Guojun Wang, Jianer Chen

“…So, to avoid this huge problem, this paper focuses on detecting fake vaccine certificates using a bot powered by Artificial Intelligence and neurologically powered by Deep Learning in which the following are the stages: a) Data Collection, b) Preprocessing to remove noise from the data, and convert to grayscale and normalised, c) Error level analysis, d) Texture‐based feature extraction for extracting logo, symbol and for the signature we extract Crest‐Trough parameter, and e) Classification using DenseNet201 and thereby giving the results as fake/real certificate. …”
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An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…This improves both the precision and efficiency of convergence while reducing the likelihood of the “two steps forward, one step back” phenomenon. This problem offers a more precise solution. Finally, these selected features are fed to the proposed classification model. …”
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Parking space number detection with multi‐branch convolution attention by Yifan Guo, Jianxun Zhang, Yuting Lin, Jie Zhang, Bowen Li

“…Since no scholar has proposed a high‐performance method for such problems, a parking space number detection model based on the multi‐branch convolutional attention is presented. …”
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Optical fiber eavesdropping detection method based on machine learning by Xiaolian CHEN, Yi QIN, Jie ZHANG, Yajie LI, Haokun SONG, Huibin ZHANG

“…Optical fiber eavesdropping is one of the major hidden dangers of power grid information security,but detection is difficult due to its high concealment.Aiming at the eavesdropping problems faced by communication networks,an optical fiber eavesdropping detection method based on machine learning was proposed.Firstly,seven-dimensions feature vector extraction method was designed based on the influence of eavesdropping on the physical layer of transmission.Then eavesdropping was simulated and experimental feature vectors were collected.Finally,two machine learning algorithms were used for classification detection and model optimization.Experiments show that the performance of the neural network classification is better than the K-nearest neighbor classification,and it can achieve 98.1% eavesdropping recognition rate in 10% splitting ratio eavesdropping.…”
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Network-based intrusion detection using deep learning technique by Muhammad Farhan, Hafiz Waheed ud din, Saadat Ullah, Muhammad Sajjad Hussain, Muhammad Amir Khan, Tehseen Mazhar, Umar Farooq Khattak, Ines Hilali Jaghdam

“…The interesting novelty of this study is the tactical use of ReLU-based DNN combined with feature optimization through the Extra Tree Classifier, which not only overcomes general problems like vanishing gradients and overfitting but also greatly increases the interpretability of the model and the efficiency of its computation. …”
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Tampered text detection via RGB and frequency relationship modeling by Yuxin WANG, Boqiang ZHANG, Hongtao XIE, Yongdong ZHANG

“…In recent years, the widespread dissemination of tampered text images on the Internet constitutes an important threat to the security of text images.However, the corresponding tampered text detection (TTD) methods have not been sufficiently explored.The TTD task aims to locate all text regions in an image while judging whether the text regions have been tampered with according to the authenticity of the texture.Thus, different from the general text detection task, TTD task further needs to perceive the fine-grained information for real-world and tampered text classification.TTD task has two main challenges.One the one hand, due to the high similarity in texture between real-world texts and tampered texts, TTD methods that only learn from RGB domain features have limited capability to distinguish these two-category texts well.On the other hand, as the different detecting difficulty exists in real-world texts and tampered texts, the network cannot well balance the learning process of the two-category texts, resulting in the imbalance detection performance between real-world and tampered texts.Compared with RGB domain features, the discontinuity of text texture in frequency domain can help the network to identify the authenticity of text instances.Accordingly, a new TTD method based on RGB and frequency information relationship modeling was proposed.The features in the RGB and frequency domains were extracted by independent feature extractors respectively.Thus, the identification ability of tampered texture can be enhanced by introducing frequency information during the texture perception.Then, a global RGB-frequency relationship module (GRM) was introduced to model the texture authenticity relationship between different text instances.GRM referred to the RGB-frequency features of other text instances in the same image to assist in judging the authenticity of the current text instance, which solved the problem of imbalanced detection performance.Furthermore, a new TTD dataset (Tampered-SROIE) was proposed to evaluate the effectiveness of proposed method, which contains 986 images (626 training images and 360 test images).By evaluating on the Tampered-SROIE, the proposed method obtains 95.97% and 96.80% in F-measure for real-world and tampered texts respectively and reduces the imbalanced detection accuracy by 1.13%.The proposed method will give new insights to the TTD community from the perspective of network structure and detection strategy.Tampered-SROIE also provides an evaluation benchmark for future TTD methods.…”
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Multitask semantic change detection guided by spatiotemporal semantic interaction by Yinqing Wang, Liangjun Zhao, Yueming Hu, Hui Dai, Yuanyang Zhang

“…However, existing SCD methods often neglect the spatial details and temporal dependencies of dual-time images, leading to problems such as change category imbalance and limited detection accuracy, especially in capturing small target changes. …”
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Human face localization and detection in highly occluded unconstrained environments by Abdulaziz Alashbi, Abdul Hakim H.M. Mohamed, Ayman A. El-Saleh, Ibraheem Shayea, Mohd Shahrizal Sunar, Zieb Rabie Alqahtani, Faisal Saeed, Bilal Saoud

“…This study presents a new methodology, which incorporates an advanced occluded face detection (OFD) model, in order to enhance feature extraction and detection network. …”
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Features of human papillomavirus infection frequency in different regions of the Russian Federation (literature review) by E. V. Belyaeva, O. A. Tokarskaya, T. A. Bairova

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Subtelomeric screening in Serbian children with dysmorphic features and unexplained developmental delay/intellectual disabilities by Tatjana Damnjanovic, Vladimir Kostic, Ida Jovanovic, Valerija Dobricic, Tatjana Varljen, Vera Bunjevacki, Ljiljana Lukovic, Biljana Jekic, Vesna Mitic, Nikola Dimitrijevic, Nela Maksimovic, Goran Cuturilo, Ivana Novakovic

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Features of Surgical Correction of Spontaneous Luxation of the Complex “IOL Posterior Chamber – Capsular Bag” by O. P. Mishchenko, N. A. Senchenko, A. G. Shchuko

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Clinical features and molecular genetic risk factors for the development of chronic bronchitis in adolescent smokers. by S. I. Ilchenko, A. А. Fialkovska

“…Chronic bronchitis (СB) remains one of the most pressing problems of pediatric pulmonology. This is due to the high prevalence of this disease and the possible transformation into chronic obstructive pulmonary disease (COPD) in adults. …”
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Features of the organizational concept of airspace management planning in the Russian Federation on the example of the Moscow airspace by V. K. Pechenezhsk, E. K. Chuvikovskaya

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