CNN–Transformer Hybrid Architecture for Underwater Sonar Image Segmentation by Juan Lei, Huigang Wang, Zelin Lei, Jiayuan Li, Shaowei Rong

“…FLSSNet is built upon a CNN and Transformer backbone network, integrating four core submodules to address various technical challenges: (1) The asymmetric dual encoder–decoder (ADED) is capable of simultaneously extracting features from different modalities and systematically modeling both local contextual information and global spatial structure. (2) The Transformer feature converter (TFC) module optimizes the multimodal feature fusion process through feature transformation and channel compression. (3) The long-range correlation attention (LRCA) module enhances CNN’s ability to model long-range dependencies through the collaborative use of convolutional kernels, selective sequential scanning, and attention mechanisms, while effectively suppressing noise interference. (4) The recursive contour refinement (RCR) model refines edge contour information through a layer-by-layer recursive mechanism, achieving greater precision in boundary details. …”
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A novel method based on the SCNGO‐ICEEMDAN and MCNN‐BiLSTM model for fault diagnosis of motor bearings for more electric aircraft by Dongsheng Yuan, Feng Liu, Zhonggang Yin, Yanqing Zhang, Yanping Zhang, Peien Luo

“…Then, a multi‐scale convolutional neural network (MCNN) is used to extract the time–frequency domain features of the de‐noised signal and perform information fusion. …”
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TSNetIQ: High-Resolution DOA Estimation of UAVs Using Microphone Arrays by Kequan Zhu, Tian Jin, Shitong Xie, Zixuan Liu, Jinlong Sun

“…Experiments are conducted to evaluate the proposed method under different signal-to-noise ratios (SNRs), sampling frequencies, and array configurations. …”
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Space Precession Target Classification Based on Radar High-Resolution Range Profiles by Yizhe Wang, Cunqian Feng, Yongshun Zhang, Sisan He

“…This paper presents two methods for classifying different types of space precession targets from the HRRPs. …”
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Digital Twin Network-Based 6G Self-Evolution by Yuhong Huang, Mancong Kang, Yanhong Zhu, Na Li, Guangyi Liu, Qixing Wang

“…Specifically, the proposed architecture introduces a key concept called “future shots” that gives accurate network predictions under different time scales of self-evolution strategies for various network elements. …”
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CNN Based Automatic Speech Recognition: A Comparative Study by Hilal Ilgaz, Beyza Akkoyun, Özlem Alpay, M. Ali Akcayol

“…The most advanced results have been obtained with speech recognition systems created using convolutional neural network (CNN) and recurrent neural networks (RNN). …”
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Sound Quality Prediction Method of Dual-Phase Hy-Vo Chain Transmission System Based on MFCC-CNN and Fuzzy Generation by Jiabao LI, Lichi AN, Yabing CHENG, Haoxiang WANG

“…The convolutional neural network (CNN) is developed, utilizing MFCC feature maps as inputs and evaluation scores as outputs. …”
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Modeling Marine Geoid in the China Seas and Its Adjacent Ocean Based on Satellite Altimeter-Derived Gravity Anomaly Model by Huiying Zhang, Xin Liu, Zhen Li, Xiaotao Chang, Heping Sun, Hui Li, Jinyun Guo

“…The Stokes formula is employed in this study to construct the geoid model, while the two-dimensional fast Fourier transform convolution in planar coordinate is utilized to enhance computational efficiency. …”
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Semi-Supervised Atmospheric Turbulence Mitigation Based on Hybrid Models by Wenhao Chu, Zhi Cheng, Lixin He

“…Secondly, a simple convolutional neural network containing a lightweight feature extraction residual module was used for deblurring. …”
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A Machine Learning Model for Procurement of Secondary Reserve Capacity in Power Systems with Significant vRES Penetrations by João Passagem dos Santos, Hugo Algarvio

“…Benchmark and test data are from the year 2024. Different machine learning architectures have been tested, but a Fully Connected Neural Network (FCNN) has the best results. …”
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Spatiotemporal DeepWalk Gated Recurrent Neural Network: A Deep Learning Framework for Traffic Learning and Forecasting by Jian Yang, Jinhong Li, Lu Wei, Lei Gao, Fuqi Mao

“…Three publicly available datasets with different time granularities of 15, 30, and 60 min are used to validate the short- and long-time prediction effect of this model. …”
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Multiclass Incremental Learning for Fault Diagnosis in Induction Motors Using Fine-Tuning with a Memory of Exemplars and Nearest Centroid Classifier by Magdiel Jiménez-Guarneros, Jonas Grande-Barreto, Jose de Jesus Rangel-Magdaleno

“…This article presents a multiclass incremental learning (MCIL) framework based on 1D convolutional neural network (CNN) for fault detection in induction motors. …”
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Efficient dataset extension using generative networks for assessing degree of coating degradation around scribe by Dominik Stursa, Pavel Rozsival, Petr Dolezel

“…A novel methodology for dataset augmentation in the semantic segmentation of coil-coated surface degradation is presented in this study. Deep convolutional generative adversarial networks (DCGAN) are employed to generate synthetic input-target pairs, which closely resemble real-world data, with the goal of expanding an existing dataset. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…The study employs Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) to capture complex spatial and temporal patterns, enabling more accurate and timely drought forecasting compared to traditional approaches. …”
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Comparative Analysis of MTCNN and Haar Cascades for Face Detection in Images with Variation in Yaw Poses and Facial Occlusions by Omer Abdulhaleem Naser, Sharifah Mumtazah, Khairulmizam Samsudin, Marsyita Hanafi, Siti Mariam Binti, Nor Zarina Zamri

“…Haar Cascades and Multi-task Cascaded Convolutional Networks (MTCNN) are compared for facial pose variation robustness. …”
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A WiFi RSSI ranking fingerprint positioning system and its application to indoor activities of daily living recognition by Zixiang Ma, Bang Wu, Stefan Poslad

“…Second, Kendall tau correlation coefficient and a convolutional neural network are applied to extract the ranking features for estimating locations. …”
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UAV Small Target Detection Model Based on Dual Branches and Adaptive Feature Fusion by Guogang Wang, Mingxing Gao, Yunpeng Liu

“…Finally, in order to focus on the target area more accurately, we introduce the large separable kernel attention mechanism into the convolutional layer to provide it with a richer and more comprehensive feature representation, which significantly improves the detection accuracy of targets of different scales. …”
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Improvement of Multiclass Classification of Pavement Objects Using Intensity and Range Images by Elham Eslami, Hae-Bum Yun

“…Motivated by the need for an improved pavement objects classification, we present Dual Attention Convolutional Neural Network (DACNN) to improve the performance of multiclass classification using intensity and range images collected with 3D laser imaging devices. …”
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A deep neural network with attention mechanism for flow prediction of compressor blade by Guanyu Gao, Gang Wang

“…Mach number flow fields under different working conditions are predicted using the proposed model, and the prediction is well consistent with CFD results. …”
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Music Similarity Detection Through Comparative Imagery Data by Asli Saner, Min Chen

“…With the aid of feature-based analysis and data visualization, we conducted experiments to analyze how different music features may contribute to the judgment of plagiarism. …”
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