Optimized Multi-Scale Detection and Numbering of Teeth in Panoramic Radiographs Using DentifyNet by Salih Taha Alperen Ozcelik, Huseyin Uzen, Abdulkadir Sengur, Muammer Turkoglu, Adalet Celebi, Nebras M. Sobahi

“…DentifyNet integrates a customized Faster R-CNN framework with Feature Pyramid Networks (FPN), flexible anchor structures, and RoI Align to enhance detection precision. …”
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Enhancing Road Scene Segmentation With an Optimized DeepLabV3+ by Zhe Ren, Libao Wang, Tianming Song, Yihang Li, Jian Zhang, Fengfeng Zhao

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Classification of musculoskeletal pain using machine learning by Dalia Mohamed Fouad, Marwa Mahmoud Mahfouz, Mohammed Mostafa Mohamed, Mahmoud Yassin Elzanaty, Tarek Abd El-Hafeez

“…The proposed framework involves data preprocessing, definition of neural network architecture, implementation of PSO, and performance evaluation. …”
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Deep Learning Model for Analyzing EEG Signal Analysis by Varun Gupta, Vivek Kumar, Prince, Saurabh Singh, Young-Seok Lee, In-Ho Ra

“…It comprises pre-processing, feature extraction, feature selection, and classification stages. …”
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Digital Biomarkers for Diagnosis of Muscle Disorders Using Stimulated Muscle Contraction Signal by Kwangsub Song, Sangui Choi, Jin-Hong Shin, Woo-Hyeon Son, Hyuntae Park, Hooman Lee, Nam-Jong Paik

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DOOSRA—Distributed Object‐Oriented Software Restructuring Approach using DIM‐K‐means and MAD‐based ENRNN classifier by G. Sudhakar, S. Nithiyanandam

“…After that, from the graph, the extraction of significant features is done. Utilising a multi variant objective‐based Aquila optimiser, the most pertinent features are selected as of the extracted features. …”
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Combining readily available population and land cover maps to generate non-residential built-up labels to train Sentinel-2 image segmentation models by Diogo Duarte, Cidália C. Fonte

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Making Images Speak: Human-Inspired Image Description Generation by Chifaa Sebbane, Ikram Belhajem, Mohammed Rziza

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An automatic approach to detect skin cancer utilizing active infrared thermography by Ricardo F. Soto, Sebastián E. Godoy

“…These features were implemented in a support-vector machine classifier to detect malignancy. …”
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Where We Rate: The Impact of Urban Characteristics on Digital Reviews and Ratings by Özge Öztürk Hacar, Müslüm Hacar, Fatih Gülgen, Luca Pappalardo

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Seismic Foresight: A Novel Multi-Input 1D Convolutional Mixer Model for Earthquake Prediction Using Ionospheric Signals by Hakan Uyanik, Mehmet Kokum, Erman Senturk, Mohamed Freeshah, Salih T. A. Ozcelik, Muhammed Halil Akpinar, Serenay Celik, Abdulkadir Sengur

“…The model architecture features depth-wise and point-wise convolutions with patch embedding, utilizing uses four tunable hyperparameters: network depth, hidden dimension size, kernel size, and patch size. …”
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Conformal On-Body Antenna System Integrated with Deep Learning for Non-Invasive Breast Cancer Detection by Marwa H. Sharaf, Manuel Arrebola, Khalid F. A. Hussein, Asmaa E. Farahat, Álvaro F. Vaquero

“…A multi-branch neural network processes these features to achieve precise tumor localization and size estimation. …”
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A Risk Assessment Analysis to Enhance the Security of OT WAN with SD-WAN by Van Joshua Abergos, Faiza Medjek

“…The obtained results demonstrated that software-defined wide area network (SD-WAN) has the best security features that even overshadow its vulnerabilities to perform not just as a WAN solution but as a security solution against DoV, DoC, and DoS. …”
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EmbryoNet-VGG16 framework for deep learning-based embryo classification with Otsu segmentation by M. Saraniya, J. Anitha Ruth

“…The authors develop EmbryoNet-VGG16, a system that functions as an automated embryo quality evaluation tool, combining Otsu segmentation with a modified Visual Geometry Group-16 (VGG16) Convolutional Neural Network (CNN) architecture. …”
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Motor imagery EEG signal classification using novel deep learning algorithm by Sathish Mathiyazhagan, M. S. Geetha Devasena

“…For final feature classification, an adaptive deep belief network (ADBN) is proposed. …”
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YOLOv8-RD: High-Robust Pine Wilt Disease Detection Method Based on Residual Fuzzy YOLOv8 by Junchao Yuan, Lina Wang, Tingting Wang, Ali Kashif Bashir, Maryam M. Al Dabel, Jiaxing Wang, Hailin Feng, Kai Fang, Wei Wang

“…We synthesized the benefits of residual learning and fuzzy deep neural networks to develop a residual fuzzy module (ResFuzzy), which adeptly filters image noise and refines background features with enhanced smoothness. …”
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An Evolutionary Deep Reinforcement Learning-Based Framework for Efficient Anomaly Detection in Smart Power Distribution Grids by Mohammad Mehdi Sharifi Nevisi, Mehrdad Shoeibi, Francisco Hernando-Gallego, Diego Martín, Sarvenaz Sadat Khatami

“…To address these challenges, this study proposes a novel deep reinforcement learning (DRL)-based framework, integrating a convolutional neural network (CNN) for hierarchical feature extraction and a recurrent neural network (RNN) for sequential pattern recognition and time-series modeling. …”
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NeuroFuzDetect–A Neural and Fuzzy Inference System for Fake News Classification by Borra Vineetha, Munirathinam Nirmala

“…NeuroFuzDetect leverages advanced computational reasoning to analyze uncertainty and ambiguity in textual data by evaluating critical linguistic features, including credibility, emotional tone, and language patterns, ensuring interpretability by providing justifications for its predictions. …”
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Predicting the Behavior of Road Users in Rural Areas for Self-Driving Cars by S. A. Ivanov, B. Rasheed

“…Another proposed feature is to use an adapted loss function that penalizes the network for generating trajectories that go beyond the drivable area. …”
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Machine Learning-Based Expression Generation Technology for Virtual Characters in Film and Television Art by Yi Zhang, Junting Qian

“…The ML-EGM model uses spatial and temporal features to generate expression by integrating generative adversarial networks, transformer encoding, and lip synchronization. …”
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