Modern Approaches to Detect and Classify Comment Toxicity Using Neural Networks by Sergey V. Morzhov

“…It is a non-trivial task even if the word “understand” here means only “to classify”. the rapid evolution of machine learning technologies has led to ubiquitous implementation of new algorithms. A lot of tasks, which for many years were considered almost impossible to solve, are now quite successfully solved using deep learning technologies. this article considers algorithms built using deep learning technologies and neural networks which can successfully solve the problem of detection and classification of toxic comments. …”
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Detection of weak multi-target with adjacent frequency based on chaotic system by Dawei Chen, Shuo Shi, Xuemai Gu, Byonghyo Shim, Qianyao Ren

“…To address these problems, in this article, we focus on the weak multi-target detection with adjacent frequency under the narrow-band noise, and a novel chaotic detection system that integrates the detection algorithm based on period-chaos duration ratio is proposed. …”
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Detecting and Explaining Postpartum Depression in Real-Time with Generative Artificial Intelligence by Silvia García-Méndez, Francisco de Arriba-Pérez

“…Moreover, it addresses the black box problem since the predictions are described to the end users thanks to the combination of LLMS with interpretable ML models (i.e. tree-based algorithms) using feature importance and natural language. …”
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Overheating Defect Detection of Composite Insulator Based on Mask R-CNN by Yi GAO, Lianfang TIAN, Qiliang DU

“…Aiming at the problems of large workload and low intelligence of the current infrared image-based overheating defect detection techniques for composite insulators, and the poor accuracy and poor generalization performance of the traditional image segmentation methods in complex backgrounds, an overheating defect detection method is proposed for composite insulators based on instance segmentation network Mask R-CNN. …”
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Hybrid attention transformer integrated YOLOV8 for fruit ripeness detection by Jianyin Tang, Zhenglin Yu, ChangShun Shao

“…Abstract The complexity of the outdoor orchard environment, especially the changes in light intensity and the shadows generated by fruit clusters, present challenges in the identification and classification of mature fruits. To solve these problems, this paper proposes an innovative fruit recognition model, HAT-YOLOV8, aiming to combine the advantages of Hybrid Attention Transformer (HAT) and YOLOV8 deep learning algorithm. …”
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Early detection of plant leaf diseases using stacking hybrid learning. by Abdullah Sheneamer

“…Various approaches have been used to identify diseases, including image processing and sophisticated algorithms. The most effective method of disease identification from crops is automatic detection using methods of image processing and classification algorithms for the diseases to be categorised based on different picture attributes. …”
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Ensemble-RNN: A Robust Framework for DDoS Detection in Cloud Environment by Asha Varma Songa, Ganesh Redy Karri

“…This paper proposes an intrusion detection framework using Ensemble feature selection with RNN (ERNN) to tackle the problem at hand. …”
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Combining Physical and Network Data for Attack Detection in Water Distribution Networks by Côme Frappé - - Vialatoux, Pierre Parrend

“…This paper addresses this problem by providing a multi-layer approach to applying machine learning to cyber-physical systems, by combining physical and network traffic data and assessing their effects on the attack detection performance of machine learning algorithms, as well as the cross-impact with data enriched with graph metrics.…”
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Adaptive Multi-Radar Anti-Bias Track Association Algorithm Based on Reference Topology Features by Shaoming Wei, Xuan Zhou, Jun Wang, Rui Pang, Xueqing Li, Qiang Liu

“…To address the track association problem in multi-radar systems, particularly the challenges posed by offset bias, this paper proposes an adaptive multi-radar anti-bias track association algorithm based on reference topological features (RETs) that achieves accurate association despite offset bias and radar missed detections. …”
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Current Transformer Saturation Detection Method Based on Artificial Neural Network by Yu. V. Rumiantsev

“…And since, when using classical electromagnetic current transformer, it is impossible to exclude the possibility of its saturation, the detection of such abnormal condition is an urgent technical problem. …”
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Research on the Computed Tomography Pebble Flow Detecting System for HTR-PM by Xin Wan, Ximing Liu, Jichen Miao, Peng Cong, Yuai Zhang, Zhifang Wu

“…Pebble dynamics is important for the safe operation of pebble-bed high temperature gas-cooled reactors and is a complicated problem of great concern. To investigate it more authentically, a computed tomography pebble flow detecting (CT-PFD) system has been constructed, in which a three-dimensional model is simulated according to the ratio of 1 : 5 with the core of HTR-PM. …”
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Lightweight network for insulator fault detection based on improved YOLOv5 by Dehua Weng, Zhiliang Zhu, Zhengbing Yan, Moran Wu, Ziang Jiang, Nan Ye

“…To address these issues, we introduce a novel one-stage network that enables real-time detection of insulator faults on mobile devices. We designed a new module that optimises the computational complexity of networks and fused the module with the attention mechanism SimAM to solve the problem of low efficiency in detecting flashover faults. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…For regression and classification, deep neural network (DNN) from deep learning algorithms and support vector machine (SVM), decision trees (DTs), k-nearest neighbor (KNN), random forest (RF), logistic regression (LR), and extreme gradient boosting (XGBoost) algorithms from machine learning algorithms were used. …”
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Iterative PolInSAR Target Decomposition for Scattering Characterization and Building Detection by Di Zhuang, Lamei Zhang, Bin Zou

“…In densely rotated built-up areas, restricted by interactive and complex scatterings, most polarimetric synthetic aperture radar scattering analyses and unsupervised building detection algorithms have failed, especially under conditions of large radar look angles. …”
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Comparative Analysis of Deep Learning Models for Intrusion Detection in IoT Networks by Abdullah Waqas, Sultan Daud Khan, Zaib Ullah, Mohib Ullah, Habib Ullah

“…This study addresses the problem of detecting intrusions in IoT environments by evaluating the performance of deep learning (DL) models under different data and algorithmic conditions. …”
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A Lightweight YOLO-Based Architecture for Apple Detection on Embedded Systems by Juan Carlos Olguín-Rojas, Juan Irving Vasquez, Gilberto de Jesús López-Canteñs, Juan Carlos Herrera-Lozada, Canek Mota-Delfin

“…In Mexico, the manual detection of damaged apples has led to inconsistencies in product quality, a problem that can be addressed by integrating vision systems with machine learning algorithms. …”
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Infrared dim tiny-sized target detection based on feature fusion by Peng Zhang, Yaman Jing, Guodong Liu, Ziyang Chen, Xiaoyan Wu, Osami Sasaki, Jixiong Pu

“…These two main modules are employed as the core to form a feature fusion network to realize the detection of infrared dim tiny-sized targets. The comparison of the proposed network with other algorithms are performed on open-source dataset and experimentally generated infrared images. …”
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Case-Based Approach to Detect Cancer in Women with Curative Intent at Beginning by Imran Majeed, Ahmad Imran, Mazhar Hussain, Mubahir Ali Syed, Tuba Zainab, Hamza Waheed, Tayyaba Dawood, Iqra Danish, Maryam Zeb, Kashif Hameed, Mehreen Farooq, Fatima Amjad, Razia Faqeer, Maria Abdullah

“…Objective: To Increase the detection rate of mammography for detection of early breast cancer. …”
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Blockchain-Enabled Deep Recurrent Neural Network Model for Clickbait Detection by Abdul Razaque, Bandar Alotaibi, Munif Alotaibi, Fathi Amsaad, Ansagan Manasov, Salim Hariri, Banu B. Yergaliyeva, Aziz Alotaibi

“…To achieve the clickbait analysis and source rating, the detection of blocklisted/allowlisted source and source rating check algorithms are introduced. …”
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THE PROBLEMS OF PROVIDING INFECTIOUS DISEASE SAFETY FOR ORGAN AND TISSUE DONATION BY SCREENING BLOOD-BORNE VIRAL INFECTIONS by M. Sh. Khubutiya, S. A. Solonin, M. A. Godkov

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