A non-sub-sampled shearlet transform-based deep learning sub band enhancement and fusion method for multi-modal images by Sudhakar Sengan, Praveen Gugulothu, Roobaea Alroobaea, Julian L. Webber, Abolfazl Mehbodniya, Amr Yousef

“…To address these limitations, this study proposes a novel fusion framework that integrates the Non-Subsampled Shearlet Transform (NSST) with a Convolutional Neural Network (CNN) for effective sub-band enhancement and image reconstruction. …”
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Diagnosis of Lung Cancer Using Endobronchial Ultrasonography Image Based on Multi-Scale Image and Multi-Feature Fusion Framework by Huitao Wang, Takahiro Nakajima, Kohei Shikano, Yukihiro Nomura, Toshiya Nakaguchi

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Enhancing water saturation predictions from conventional well logs in a carbonate gas reservoir with a hybrid CNN-LSTM model by Ali Gohari Nezhad, Mohammad Emami Niri

“…Four machine learning algorithms: XGBoost, long short-term memory (LSTM), 1-dimensional convolutional neural network (1D-CNN), and a hybrid CNN-LSTM were developed to predict experimental water saturation values from conventional well logs. …”
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Categorical classification of skin cancer using a weighted ensemble of transfer learning with test time augmentation by Aliyu Tetengi Ibrahim, Mohammed Abdullahi, Armand Florentin Donfack Kana, Mohammed Tukur Mohammed, Ibrahim Hayatu Hassan

“…Considering the inability of dermatologists to diagnose skin cancer accurately, a convolutional neural network (CNN) approach was used for skin cancer diagnosis. …”
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Novel deep learning for multi-class classification of Alzheimer’s in disability using MRI datasets by Sumaiya Binte Shahid, Maleeha Kaikaus, Md. Hasanul Kabir, Mohammad Abu Yousuf, A. K. M. Azad, A. S. Al-Moisheer, Naif Alotaibi, Salem A. Alyami, Touhid Bhuiyan, Mohammad Ali Moni, Mohammad Ali Moni, Mohammad Ali Moni

“…IntroductionAlzheimer’s disease (AD) is one of the most common neurodegenerative disabilities that often leads to memory loss, confusion, difficulty in language and trouble with motor coordination. …”
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TCN-GRU Based on Attention Mechanism for Solar Irradiance Prediction by Zhi Rao, Zaimin Yang, Xiongping Yang, Jiaming Li, Wenchuan Meng, Zhichu Wei

“…The global horizontal irradiance (GHI) is the most important metric for evaluating solar resources. …”
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Two-Stage Video Violence Detection Framework Using GMFlow and CBAM-Enhanced ResNet3D by Mohamed Mahmoud, Bilel Yagoub, Mostafa Farouk Senussi, Mahmoud Abdalla, Mahmoud Salaheldin Kasem, Hyun-Soo Kang

“…The proposed approach effectively combines GMFlow-generated optical flow with deep 3D convolutional networks, providing robust and efficient detection of violence in videos.…”
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A Self-Attention Enhanced Deep CNN-LSTM-Based Irregular Surface Recognition Approach for Integration Into Lower Limb Prosthesis Systems to Ensure Safety Through Predictive Walking by Norazian Subari, Kamarul Hawari Ghazali, Yuanfa Ji

“…However, significant challenges persist when users encounter irregular surfaces, as most prosthetic systems lack the capability to dynamically adapt to surface variations. …”
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Multistage adaptive cyberattack in power systems with CNN identification feedback loops by Mohannad Alhazmi, Alexis Pengfei Zhao, Xi Cheng, Chenlu Yang

“…The proposed CDB-TAS model comprises: (i) a Preliminary Reconnaissance Phase, where a Convolutional Neural Network (CNN) identifies the most vulnerable buses via real-time anomaly detection; (ii) an Escalation Phase, where a Double Deep Q-Network (Double DQN) dynamically refines the attack strategy based on grid response and demand profiles; and (iii) a Sustained Attack Phase, which maintains high-intensity disruptions while minimizing detection through continuous feedback adaptation. …”
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SGCL-LncLoc: An Interpretable Deep Learning Model for Improving lncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning by Min Li, Baoying Zhao, Yiming Li, Pingjian Ding, Rui Yin, Shichao Kan, Min Zeng

“…Then, SGCL-LncLoc applies graph convolutional networks to learn the comprehensive graph representation. …”
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A prediction model for the mechanical properties of SUS316 stainless steel ultrathin strip driven by multimodal data mixing by Zhenhua Wang, Pengzhan Wang, Yunfei Liu, Yuanming Liu, Tao Wang

“…Specifically, the MLP branch is used to extract the rolling process data features, and the ResNet with the addition of a convolutional block attention module (CBAM) is used to extract the microstructure features. …”
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Radiative Transfer Model-Integrated Approach for Hyperspectral Simulation of Mixed Soil-Vegetation Scenarios and Soil Organic Carbon Estimation by Asmaa Abdelbaki, Robert Milewski, Mohammadmehdi Saberioon, Katja Berger, José A. M. Demattê, Sabine Chabrillat

“…A simulated EO disturbed soil spectral library (DSSL) was created, significantly expanding the EU LUCAS cropland soil spectral library. A 1D convolutional neural network (1D-CNN) was trained on this database to predict Soil Organic Carbon (SOC) content. …”
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INFORMATION IMAGE MODEL by Evgeniy V. Yurkevich

“…A model of a convolution of information in the form of image and symbol. …”
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A systematic review of multimodal fake news detection on social media using deep learning models by Maged Nasser, Noreen Izza Arshad, Abdulalem Ali, Hitham Alhussian, Faisal Saeed, Aminu Da'u, Ibtehal Nafea

“…The findings showed that the Transformer models and Recurrent Neural Networks (RNNs) are the most popular deep learning techniques for detecting multimodal fake news, followed by the Convolutional Neural Networks (CNNs) techniques. …”
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Forecasting very short-term power load with hybrid interpretable deep models by Zhihe Yang, Jiandun Li, Chang Liu, Haitao Wang

“…Experiment results demonstrate that the hybrid model based on Convolutional Neural Network (CNN) and BiLSTM outperforms several state-of-the-art solutions. …”
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Accurate and real-time brain tumour detection and classification using optimized YOLOv5 architecture by M. Saranya, R. Praveena

“…This study performs the prediction and classification of brain tumours present in MRI, a combined classification and localization framework model is proposed connecting Fully Convolutional Neural Network (FCNN) and You Only Look Once version 5 (YOLOv5). …”
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EFCNet enhances the efficiency of segmenting clinically significant small medical objects by Lingjie Kong, Qiaoling Wei, Chengming Xu, Xiaofeng Ye, Wei Liu, Min Wang, Yanwei Fu, Han Chen

“…Notably, smaller objects benefit most, highlighting EFCNet’s effectiveness where conventional models underperform. …”
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Alzheimer’s Prediction Methods with Harris Hawks Optimization (HHO) and Deep Learning-Based Approach Using an MLP-LSTM Hybrid Network by Raheleh Ghadami, Javad Rahebi

“…<b>Method:</b> This proposal methodology involves sourcing Alzheimer’s disease-related MRI images and extracting features using convolutional neural networks (CNNs) and the Gray Level Co-occurrence Matrix (GLCM). …”
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Computational methods and technical means of processing signals of side electromagnetic emanation by Danil A. Shinyaev, Leonid N. Kessarinskiy, Egor A. Simakhin

“…The proposed solution to the problem is to transform the reconstructed image into the original one by training the model on a convolutional neural network. Despite its effectiveness, this approach requires careful mathematical analysis of spurious emissions. …”
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Autonomous detection of nail disorders using a hybrid capsule CNN: a novel deep learning approach for early diagnosis by Gunjan Shandilya, Sheifali Gupta, Salil Bharany, Ateeq Ur Rehman, Upinder Kaur, Hafizan Mat Som, Seada Hussen

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