Ignition delay prediction for fuels with diverse molecular structures using transfer learning-based neural networks by Mo Yang, Dezhi Zhou

“…A comprehensive dataset of ignition delays was generated using a random sampling technique across different temperatures and pressures, focusing on hydrocarbon fuels with 1–4 carbon atoms. …”
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Dual-Channel CNN-Based Framework for Automated Rebar Detection in GPR Data of Concrete Bridge Decks by Sepehr Pashoutani, Mohammadsajjad Roudsari, Jinying Zhu

“…This paper presents two automated rebar detection algorithms based on Convolutional Neural Network (CNN) machine learning techniques. …”
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Efficient Pruning of Detection Transformer in Remote Sensing Using Ant Colony Evolutionary Pruning by Hailin Su, Haijiang Sun, Yongxian Zhao

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A comparative analysis of deep learning models for accurate spatio-temporal soil moisture prediction by Litao Zhu, Wen Dai, Jiru Huang, Zicong Luo

“…The performance was analyzed by different accuracy metrics. The results show that ConvLSTM has the lowest errors in both time series and spatio-temporal prediction. …”
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On the Question of the Applicability of Artificial Intelligence Systems to Forensic Examination of Documents and Their Requisites by A. F. Kupin, A. S. Kovalenko

“…The procedure and principles of operation of convolutional neural networks are described and, using their example, the results that can be achieved during forensic handwriting and technical forensic examinations of documents, as well as studies conducted within the framework of forensic expert activities, in particular, the identification of signs of technical forgery of documents (installation, erasure, additions, finishing) are indicated, establishing the facts of the execution of several signatures or handwritten records by one or different performers, establishing the original content of the records, fragments of which have been partially lost or distorted. …”
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Multi-branch network for double JPEG detection and localization by Ahmed M. Fouad, Hala H. Zayed, Ahmed Taha

“…JPEG image tampering often involves recompression with a different quantization table, known as double JPEG compression. …”
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Global information aware network with global interaction graph attention for infrared small target detection by Ruimin Yang, Yidan Zhang, Guangshuai Gao, Liang Liao, Chunlei Li

“…Additionally, the multi‐scale context fusion module utilises self‐attention and dilation convolution to complement richer feature details at different scales. …”
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An Attention-Based Spatial-Spectral Joint Network for Maize Hyperspectral Images Disease Detection by Jindai Liu, Fengshuang Liu, Jun Fu

“…The model contains 3D and 2D convolutional layers that extract features from both spatial and spectral domains to improve the identification capability of hyperspectral images. …”
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Deep Learning Techniques for Detecting Morphed Face Images: A Literature Review by Pedro Morais, Ines Domingues, Jorge Bernardino

“…This paper provides a comprehensive review of the state-of-the-art of deep learning techniques employed in morphed image detection, including Convolutional Neural Networks (CNNs), Autoencoders, and Generative Adversarial Networks (GANs). …”
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Enhancing Medical Image Classification with Unified Model Agnostic Computation and Explainable AI by Elie Neghawi, Yan Liu

“…By unifying and standardizing computational models and algorithms, UMAC ensures adaptability across different data types and computational environments while incorporating state-of-the-art methodologies. …”
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Endoscopic ultrasound-based artificial intelligence for gastrointestinal subepithelial lesions by Huan Jiang, Liansong Ye, Xianglei Yuan, Qi Luo, Nuoya Zhou, Bing Hu

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Robust Simplified Modeling of Microgrid in the Context of Constructing New Power Systems by Daxing WANG, Yan Ning, Jingpei WANG, Yang XU, Jun BI, Mingbiao ZHOU, Peng WANG

“…Next, key parameter selection-based parameter identification method is applied to avoid the issue of multiple solutions in parameter identification process. Then, the convolutional neural network is used to generalize the model parameters with respect to different typical system operation conditions. …”
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High-Concentration Time-Frequency Representation and Instantaneous Frequency Estimation of Frequency-Crossing Signals by Hui Li, Xiangxiang Zhu, Yingfei Wang, Xinpeng Cai, Zhuosheng Zhang

“…Through TF data generation, the construction of a U-net, and training, the high-concentration TF representation network achieves high-resolution TF characterization of different frequency-crossing signals. The IF separation and estimation network, with its discriminant model, offers flexibility in determining the number of components within multi-component signals. …”
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Multi-species Fish Identification using Hybrid DeepCNN with Refined Squeeze and Excitation Architecture by Jansi Rani Sella Veluswami, Nivetha Panneerselvam

“…In this study, we have proposed a new method of hybrid Deep Convolutional Neural Network (CNN) along with a Support Vector Machine (SVM) for classification. …”
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Risk-Adjusted Deep Reinforcement Learning for Portfolio Optimization: A Multi-reward Approach by Himanshu Choudhary, Arishi Orra, Kartik Sahoo, Manoj Thakur

“…The actions generated by these agents are then fused by employing a convolutional neural network to provide a single risk-adjusted action. …”
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Short Text Classification Based on Enhanced Word Embedding and Hybrid Neural Networks by Cunhe Li, Zian Xie, Haotian Wang

“…Furthermore, we propose a dual-channel hybrid model based on a Gated Convolutional Neural Network (GCNN) and Bidirectional Long Short-Term Memory (BiLSTM), which jointly captures local features and long-range global dependencies. …”
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Copula entropy regularization transformer with C2 variational autoencoder and fine-tuned hybrid DL model for network intrusion detection by Srinivas Akkepalli, Sagar K

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Median interacted pigeon optimization-based hyperparameter tuning of CNN for paddy leaf disease prediction by Jasmy Davies, S. Sivakumari

“…Furthermore, to extract relevant features from images of rice leaf diseases, Convolutional Neural Networks (CNNs) require efficient hyperparameter tuning. …”
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Creating and Validating a Ground Truth Dataset of Unified Modeling Language Diagrams Using Deep Learning Techniques by Javier Torcal, Valentín Moreno, Juan Llorens, Ana Granados

“…Large, good-quality datasets containing UML diagrams are essential for different areas in the industry, research, and teaching purposes; however, few exist in the literature and it is common to find duplicate elements in the existing datasets. …”
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Semantic-Aware Remote Sensing Change Detection with Multi-Scale Cross-Attention by Xingjian Zheng, Xin Lin, Linbo Qing, Xianfeng Ou

“…As deep learning strives, Convolutional Neural Networks (CNNs) have shown their effects in image processing applications. …”
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