MSFF-Net: Multi-Sensor Frequency-Domain Feature Fusion Network with Lightweight 1D CNN for Bearing Fault Diagnosis by Miao Dai, Hangyeol Jo, Moonsuk Kim, Sang-Woo Ban

“…This study proposes MSFF-Net, a lightweight deep learning framework for bearing fault diagnosis based on frequency-domain multi-sensor fusion. …”
Get full text

Multi-Branch CNN-LSTM Fusion Network-Driven System With BERT Semantic Evaluator for Radiology Reporting in Emergency Head CTs by Selene Tomassini, Damiano Duranti, Abdallah Zeggada, Carlo Cosimo Quattrocchi, Farid Melgani, Paolo Giorgini

Get full text

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. …”
Get full text

Multimodal Fall Detection Using Spatial–Temporal Attention and Bi-LSTM-Based Feature Fusion by Jungpil Shin, Abu Saleh Musa Miah, Rei Egawa, Najmul Hassan, Koki Hirooka, Yoichi Tomioka

“…In order to address these challenges, we propose a multimodal fall detection framework that integrates skeleton and sensor data. …”
Get full text

Hybrid CNN-GRU Model for Real-Time Blood Glucose Forecasting: Enhancing IoT-Based Diabetes Management with AI by Reem Ibrahim Alkanhel, Hager Saleh, Ahmed Elaraby, Saleh Alharbi, Hela Elmannai, Saad Alaklabi, Saeed Hamood Alsamhi, Sherif Mostafa

“…To anticipate BGL many steps ahead, we propose a novel hybrid deep learning model framework based on Gated Recurrent Units (GRUs) and Convolutional Neural Networks (CNNs), which can be integrated into the Internet of Things (IoT)-enabled diabetes management systems, improving prediction accuracy and timeliness by allowing real-time data processing on edge devices. …”
Get full text

Generative Artificial Intelligence-Enabled Facility Layout Design Paradigm by Fuwen Hu, Chun Wang, Xuefei Wu

“…This research establishes a foundational framework for AI-driven facility planning, offering actionable insights for AI-enabled facility layout design adoption and highlighting future directions in the generative design of complex engineering.…”
Get full text

CFFormer: Channel Fourier Transformer for Remote Sensing Super Resolution by Zexin Xie, Jian Wang, Wei Song, Yanling Du, Huifang Xu, Qinhan Yang

Get full text

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

“…Furthermore, utilizing an inclusive dataset, a new CNN-LSTM model was constructed with a 10-fold framework, achieving an average R-squared of 0.968. …”
Get full text

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

“…Next, by utilizing the modified ResNet152V2 as a feature extractor, a Convolutional Neural Network based model, namely, the ‘IncepRes’, is proposed by fusing the Inception and ResNet architectures for multiclass classification of AD categories. …”
Get full text

Optimizing Cervical Cancer Diagnosis with Feature Selection and Deep Learning by Łukasz Jeleń, Izabela Stankiewicz-Antosz, Maria Chosia, Michał Jeleń

“…This finding underscores the potential of feature reduction techniques in creating efficient diagnostic frameworks. The study concludes that while convolutional neural networks offer robust classification capabilities, optimized handcrafted features remain a viable and cost-effective alternative, particularly when the data count is limited. …”
Get full text

SPHERE: Benchmarking YOLO vs. CNN on a Novel Dataset for High-Accuracy Solar Panel Defect Detection in Renewable Energy Systems by Kubilay Ayturan, Berat Sarıkamış, Mehmet Feyzi Akşahin, Uğurhan Kutbay

Get full text

Probabilistic Forecasting of Ground Magnetic Perturbation Spikes at Mid‐Latitude Stations by Michael Coughlan, Amy Keesee, Victor Pinto, Raman Mukundan, José Paulo Marchezi, Jeremiah Johnson, Hyunju Connor, Don Hampton

“…Two model frameworks were compared, a model trained using solar wind data from the Advanced Composition Explorer (ACE) satellite, and another model trained on both ACE and SuperMAG ground magnetometer data. …”
Get full text

Estimation of Fractal Dimension and Detection of Fake Finger-Vein Images for Finger-Vein Recognition by Seung Gu Kim, Jin Seong Hong, Jung Soo Kim, Kang Ryoung Park

“…Additionally, we propose an enhanced convolutional network for a next-dimension (ConvNeXt)-Small model with a large kernel attention module as a new spoof detector capable of distinguishing the generated fake finger-vein images. …”
Get full text

IoUT-Oriented an Efficient CNN Model for Modulation Schemes Recognition in Optical Wireless Communication Systems by M. Mokhtar Zayed, Saeed Mohsen, Abdullah Alghuried, Hassan Hijry, Mona Shokair

“…Keras and TensoFlow frameworks are used to implement the model, the CNN undergoes hyperparameter tuning and data augmentation to optimize accuracy. …”
Get full text

MPAR-RCNN: a multi-task network for multiple person detection with attribute recognition by S. Raghavendra, S. K. Abhilash, Venu Madhav Nookala, Jayashree Shetty, Praveen Gurunath Bharathi

“…To meet these demands, an efficient method that achieves both reliable detection and attribute classification in a unified framework is essential. This study introduces an innovative MTL framework designed to incorporate Multi-Person Attribute Recognition (MPAR) within a single-model architecture. …”
Get full text

Deep Learning-Based Surface Temperature Prediction for a Porous Radiant Burner Using Thermocouple-Calibrated Thermal Infrared Images by Hao-Yu Hsieh, Shenqyang Shy, Wei-Wun Wang, Yung-Chien Chou

“…All models exhibit stable and high prediction performance, achieving R2 values above 0.85 on the test set, thereby confirming the effectiveness and robustness of the proposed framework. Thus, the proposed AI-driven framework introduces an innovative and accurate approach to non-intrusive surface temperature measurements using infrared imaging.…”
Get full text

Enhancing wind turbine blade damage detection with YOLO-Wind by Zhao Zhanfang, Li Tuo

“…The architecture replaces standard convolutions with depthwise separable convolutions (DWConv) to optimize computational efficiency without compromising detection accuracy. …”
Get full text

Hybrid-CID: Securing IoT with Mongoose Optimization by S. Merlin Sheeba, R. S. Shaji

Get full text

Spatiotemporal Deformation Prediction Model for Retaining Structures Integrating ConvGRU and Cross-Attention Mechanism by Yanyong Gao, Zhaoyun Xiao, Zhiqun Gong, Shanjing Huang, Haojie Zhu

“…Therefore, this study proposes a novel deep learning framework, CGCA (Convolutional Gated Recurrent Unit with Cross-Attention), which integrates ConvGRU and cross-attention mechanisms. …”
Get full text

Multistage adaptive cyberattack in power systems with CNN identification feedback loops by Mohannad Alhazmi, Alexis Pengfei Zhao, Xi Cheng, Chenlu Yang

“…To address this gap, we propose a novel Cyberattack Design Based on CNN-DQN-Blockchain Technology for Targeted Adaptive Strategy (CDB-TAS)—a three-stage, dynamically evolving cyberattack framework tailored for hybrid hydrogen-electric networks. …”
Get full text