Capsule network approach for monkeypox (CAPSMON) detection and subclassification in medical imaging system by M. Nuthal Srinivasan, Mohamed Yacin Sikkandar, Maryam Alhashim, M. Chinnadurai

“…Addressing the shortcomings of traditional Machine Learning and Deep Learning models, our ESACN model utilizes the dynamic routing and spatial hierarchy capabilities of CapsNets to differentiate complex patterns such as those seen in monkeypox, chickenpox, measles, and normal skin presentations. …”
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Classification Model for Bot-IoT Attack Detection Using Correlation and Analysis of Variance by Firgiawan Faira, Dandy Pramana Hostiadi

“…This research focuses on detecting Bot-IoT activity using the Bot-IoT UNSW Canberra 2018 dataset. …”
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Harnessing self-supervised learning to boost malicious traffic detection with enhanced attention by SUN Jianwen, ZHANG Bin, LI Hongyu, CHANG Heyu

“…The existing deep learning-based malicious traffic detection methods generally suffered from three main problems: labeled sample scarcity, inadequate representation of malicious behavior traffic features, and a high false positive rate due to ineffective integration of behavioral association patterns during detection. …”
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Improving Smart Grid security: Spectral and fractal analysis as tools for detecting cyberattacks by Sergey V. Kochergin, Svetlana V. Artemova, Anatoly A. Bakaev, Evgeny S. Mityakov, Zhanna G. Vegera, Elena A. Maksimova

“…This will permit the identification of cyberattacks associated with harmonic signal distortions to provide a more accurate classification of patterns characteristic of malicious impacts.Methods. …”
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Anomaly Detection in Nuclear Power Production Based on Neural Normal Stochastic Process by Linyu Liu, Shiqiao Liu, Shuan He, Kui Xu, Yang Lan, Huajian Fang

“…To ensure the safety of nuclear power production, nuclear power plants deploy numerous sensors to monitor various physical indicators during production, enabling the early detection of anomalies. Efficient anomaly detection relies on complete sensor data. …”
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TaRTLEt: Transcriptionally-active Riboswitch Tracer Leveraging Edge deTection by Sachit Kshatriya, Sarah C. Bagby

“…Here, we introduce TaRTLEt (Transcriptionally-active Riboswitch Tracer Leveraging Edge deTection), a new high-throughput tool that recovers in vivo patterns of riboswitch-mediated transcription termination from paired-end RNA-seq data using edge detection methods. …”
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Edge Convolutional Networks for Style Change Detection in Arabic Multi-Authored Text by Abeer Saad Alsheddi, Mohamed El Bachir Menai

“…The style change detection (SCD) task asks to find the positions of authors’ style changes within multi-authored texts. …”
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usfAD based effective unknown attack detection focused IDS framework by Md. Ashraf Uddin, Sunil Aryal, Mohamed Reda Bouadjenek, Muna Al-Hawawreh, Md. Alamin Talukder

“…Further, IDS trained and tested on known datasets fails in detecting zero-day or unknown attacks due to the swift evolution of attack patterns. …”
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A Novel Metaheuristic-Based Methodology for Attack Detection in Wireless Communication Networks by Walaa N. Ismail

“…By focusing on the most relevant features, this attention mechanism makes the model suitable for complex and high-dimensional traffic patterns typical of 5G communication. As in previous approaches, it eliminates the need to manually select features such as entropy, payload size, and opcode sequences. …”
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A Novel Semantic Driven Meta-Learning Model for Rare Attack Detection by Y. Annie Jerusha, S. P. Syed Ibrahim, Vijay Varadharajan

“…Traditional models often struggle with uncertain traffic patterns, reducing their reliability. This work presents a Novel Semantic-Driven Meta-Learning Model - a hybrid framework that systematically refines categorization decisions. …”
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Assessing the Potential of PlanetScope Imagery for Iron Oxide Detection in Antimony Exploration by Douglas Santos, Joana Cardoso-Fernandes, Alexandre Lima, Ana Claúdia Teodoro

“…The results were assessed through relative comparison methods, enabling both quantitative and qualitative evaluation of the spectral similarity among sensors. Spatial patterns were analyzed, and points of interest were identified and subsequently validated through fieldwork. …”
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Advanced Multi-Scale CNN-BiLSTM for Robust Photovoltaic Fault Detection by Xiaojuan Zhang, Bo Jing, Xiaoxuan Jiao, Ruixu Yao

“…This study proposes an innovative Advanced CNN-BiLSTM architecture integrating multi-scale feature extraction with hierarchical attention to enhance PV fault detection. The proposed framework employs four parallel CNN branches with kernel sizes of 3, 7, 15, and 31 to capture temporal patterns across various time scales. …”
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Detecting Malware C&C Communication Traffic Using Artificial Intelligence Techniques by Mohamed Ali Kazi

“…Their reliance on regular updates to incorporate new malware signatures or patterns means that they can only identify known banking malware variants. …”
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ADA-NAF: Semi-Supervised Anomaly Detection Based on the Neural Attention Forest by Andrey Ageev, Andrei Konstantinov, Lev Utkin

“…In this study, we present a novel model called ADA-NAF (Anomaly Detection Autoencoder with the Neural Attention Forest) for semi-supervised anomaly detection that uniquely integrates the Neural Attention Forest (NAF) architecture which has been developed to combine a random forest classifier with a neural network computing attention weights to aggregate decision tree predictions. …”
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Cross-lingual hate speech detection using domain-specific word embeddings. by Ayme Arango Monnar, Jorge Perez Rojas, Barbara Polete Labra

“…Overall, our findings indicate common patterns in how hate speech is expressed across languages and that our proposed model can capture such relationships significantly.…”
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Comprehensive fragmentation of cell-free repetitive DNA for enhanced cancer detection in plasma by Mingguang Zhang, Shuohui Dong, Wei Rao, Shiwen Mei, Gang Hu, Ling Liu, Zhen Wang, Jianqiang Tang

“…However, the exclusive fragmentation pattern of DNA-derived cell-free repetitive elements (cfREs) remains unclear.MethodsThis study enrolled 32 healthy volunteers and 112 patients with five types of cancer. …”
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Culicoides insignis in Ecuador: Molecular identification of blood meals and detection of bluetongue virus by Juan D. Mosquera, Sonia Zapata, Denis Augot

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Integration of Deep Learning and Machine Learning Techniques for Advancing the Detection of Plant Diseases by Abdul Karim, Touqeer Ahmed Jumani, Muhammad Amir Raza, Shadi Khan Baloch, Nouman Qadeer Soomro, Muhammad Masud, Muhammad Salman Saeed, Mouaaz Nahas, Aamir Ali Patoli

“…Extreme Gradient Boosting (XGBoost) and Convolutional Neural Network (CNN) algorithm were employed to detect diseases precisely. CNN derived intricate patterns from images, whereas the XGBoost algorithm is employed for precise categorization. …”
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High-resolution detection of copy number alterations in single cells with HiScanner by Yifan Zhao, Lovelace J. Luquette, Alexander D. Veit, Xiaochen Wang, Ruibin Xi, Vinayak V. Viswanadham, Yuwei Zhang, Diane D. Shao, Christopher A. Walsh, Hong Wei Yang, Mark D. Johnson, Peter J. Park

“…When applied to high-coverage scWGS data from 65 cells across 11 neurotypical human brains, HiScanner shows a superior ability to detect smaller CNAs, uncovering distinct CNA patterns between neurons and oligodendrocytes. …”
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Criminal emotion detection framework using convolutional neural network for public safety by Jay Raval, Nilesh Kumar Jadav, Sudeep Tanwar, Giovanni Pau, Fayez Alqahtani, Amr Tolba

“…In this paper, we proposed a collaborative approach to detect crime patterns and criminal emotions with the aim of enhancing judiciary decision-making. …”
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