Lightweight CNN-based seizure classification via leveraging chimera states in iEEG recordings by Fatemeh Azad, Saeed Bagheri Shouraki, Soheila Nazari, Mansun Chan

“…These images are processed by a streamlined convolutional neural network (CNN) framework, which classifies iEEG recordings into pre-ictal, ictal, and post-ictal events with robust patient-independent performance. …”
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Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

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Incorporated flexible load forecasting based on non-intrusive load monitoring: a TCN-based meta learning approach by Yun Zhang, Quanyan Shu, Feng Ding, Feng Liu, Shuiming Jiang, Wenlong Wu

“…The enhanced performance of the proposed method is attributed to the integration of feature extraction and model adaptation within a meta-learning framework.Future research could explore the incorporation of contextual information to further enhance performance.…”
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Markov-CVAELabeller: A Deep Learning Approach for the Labelling of Fault Data by Christian Velasco-Gallego, Nieves Cubo-Mateo

“…Additionally, to evaluate the accuracy of the method, a convolutional neural network (CNN) is considered as part of the fault classification task. …”
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PseudoCell: Hard Negative Mining as Pseudo Labeling for Deep Learning-Based Centroblast Cell Detection by Narongrid Seesawad, Piyalitt Ittichaiwong, Thapanun Sudhawiyangkul, Phattarapong Sawangjai, Peti Thuwajit, Paisarn Boonsakan, Supasan Sripodok, Kanyakorn Veerakanjana, Komgrid Charngkaew, Ananya Pongpaibul, Napat Angkathunyakul, Narit Hnoohom, Sumeth Yuenyong, Chanitra Thuwajit, Theerawit Wilaiprasitporn

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Research on Seismic Signal Denoising Model Based on DnCNN Network by Li Duan, Jianxian Cai, Li Wang, Yan Shi

“…To address these shortcomings, this study introduces a novel denoising approach leveraging a DnCNN network. The DnCNN framework, which integrates batch normalization with residual learning, is adept at swiftly identifying and eliminating noise from seismic signals through its residual learning capabilities. …”
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Spatio-temporal prediction of terrorist attacks based on GCN-LSTM by Yingjie Du, Ning Ding, Hongyu Lv

“…This paper introduces an innovative spatio-temporal fusion framework that combines graph convolutional network (GCN) with long short-term memory (LSTM) models. …”
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Ball Bearing Fault Diagnosis Based on Hybrid Adversarial Learning by Xiaofeng Bai, Qazi Mazhar Ul Haq, Aftab Alam Khan, Chaohui Li, Hind Alsharif, Muhammad Shahid Anwar, Chengwei Li

“…To address this issue, this study proposes a hybrid adversarial learning method that combines convolutional neural networks with a generative adversarial network framework. …”
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Complex-Valued CNN-Based Defect Reconstruction of Carbon Steel from Eddy Current Signals by Bing Chen, Tengwei Yu

“…The proposed framework employs convolution, pooling, and activation operations specifically designed within the complex-valued domain to facilitate the high-fidelity reconstruction of defect morphology as well as precise multi-class defect classification. …”
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Leveraging an ensemble of EfficientNetV1 and EfficientNetV2 models for classification and interpretation of breast cancer histopathology images by Mahdi Azmoodeh-Kalati, Hasti Shabani, Mohammad Sadegh Maghareh, Zeynab Barzegar, Reza Lashgari

“…Additionally, we propose two ensemble architectures that integrate different trained EfficientNet models. Our framework achieves a classification accuracy of 99.58%, outperforming conventional CNN models on the BreakHis dataset. …”
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Intelligent Operation and Maintenance of Wind Turbines Gearboxes via Digital Twin and Multi-Source Data Fusion by Tiantian Xu, Xuedong Zhang, Wenlei Sun, Binkai Wang

“…Specifically, it proposes a remote intelligent operation and maintenance (O&M) framework for wind turbines based on digital twin technology. …”
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Leveraging Deep Learning for Robust Structural Damage Detection and Classification: A Transfer Learning Approach via CNN by Burak Duran, Saeed Eftekhar Azam, Masoud Sanayei

“…Then, this acceleration time-history series was transformed into grayscale images, serving as inputs for a Convolutional Neural Network developed to detect and classify structural damage states. …”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

“…Methods We developed a novel hybrid model integrating convolutional neural network (CNN), Transformer, and Whale Optimization Algorithm (WOA) for arrhythmia prediction in AMI patients. …”
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A DSP–FPGA Heterogeneous Accelerator for On-Board Pose Estimation of Non-Cooperative Targets by Qiuyu Song, Kai Liu, Shangrong Li, Mengyuan Wang, Junyi Wang

“…This study presents a hardware–software co-design framework for the pose estimation of non-cooperative targets. …”
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Deep Learning for Multi-Tissue Cancer Classification of Gene Expressions (GeneXNet) by Tarek Khorshed, Mohamed N. Moustafa, Ahmed Rafea

“…We propose a deep learning framework for cancer diagnosis by developing a multi-tissue cancer classifier based on whole-transcriptome gene expressions collected from multiple tumor types covering multiple organ sites. …”
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Hybrid Deep Learning Approach for Automated Sleep Cycle Analysis by Sebastián Urbina Fredes, Ali Dehghan Firoozabadi, Pablo Adasme, David Zabala-Blanco, Pablo Palacios Játiva, Cesar A. Azurdia-Meza

“…The objective is to design a framework for automated feature extraction. To address class imbalance, an epoch-level random undersampling (E-LRUS) method is proposed, discarding full epochs from majority classes while preserving the temporal structure, unlike traditional methods that remove individual samples. …”
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VSRDiff: Learning Inter-Frame Temporal Coherence in Diffusion Model for Video Super-Resolution by Linlin Liu, Lele Niu, Jun Tang, Yong Ding

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Multi-criteria computational screening of [BMIM][DCA]@MOF composites for CO2 capture by Mengjia Sheng, Xiang Zhang, Hongye Cheng, Zhen Song, Zhiwen Qi

“…Ionic liquid (IL) can be inserted into metal organic framework (MOF) to form IL@MOF composite with enhanced properties. …”
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PatchOut: A novel patch-free approach based on a transformer-CNN hybrid framework for fine-grained land-cover classification on large-scale airborne hyperspectral images by Renjie Ji, Kun Tan, Xue Wang, Shuwei Tang, Jin Sun, Chao Niu, Chen Pan

“…Therefore, in this paper, considering the efficiency requirements for large-scale land-cover classification, a novel patch-free approach based on a Transformer-CNN hybrid (PatchOut) framework is proposed. The proposed PatchOut framework adopts an encoder-decoder architecture, enabling rapid semantic segmentation for HSI classification. …”
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Integrating deep learning and transfer learning: optimizing white blood cells classification in medical educational institutions by M. Hussein, Faten Abd El-Sattar Zahran El-Mougi

“…This study advances automated WBCs analysis through an 8-class classification framework encompassing rare but clinically critical subtypes: neutrophils, eosinophils, basophils, lymphocytes, monocytes, immature granulocytes (IGs), erythroblasts, and platelets. …”
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