Semi-Supervised Atmospheric Turbulence Mitigation Based on Hybrid Models by Wenhao Chu, Zhi Cheng, Lixin He

“…We have conducted sufficient experiments on different types of turbulence data that the proposed framework can mitigate the motion blur and geometric distortion caused by atmospheric turbulence, thus resulting in a dramatic improvement in visual quality. …”
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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

“…Experimental results reveal the proposed framework as an effective solution to incorporate and detect new induction motor faults to already known, with a high accuracy performance across different incremental phases.…”
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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

“…Moreover, the advantages and limitations of different GAN architectures for dataset expansion are explored, with specific attention to their ability to produce realistic and diverse samples. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…Moreover, the research conducts a comparative evaluation of various machine learning models to identify the most effective algorithms for different climatic zones and crop types. By enhancing the precision and reliability of drought prediction systems, this study contributes to the promotion of sustainable agriculture and climate resilience. …”
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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

“…UPM includes 100 students with different yaw angles and occlusions (masks, glasses, or both). …”
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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

“…Third, an extended Kalman filter is then used to smooth the estimated sequential locations before multi-dimensional dynamic time warping is used to match similar trajectories or paths representing activities of daily living from different or the same users that vary in time and space. …”
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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

“…DACNN also leverages multiscale input images by capturing contextual information for object classification with different sizes and shapes. DACNN contains an attention mechanism that (i) considers semantic interdependencies in spatial and channel dimensions and (ii) adaptively fuses scale-specific and mode-specific features so that each feature has its own level of contribution to the final decision. …”
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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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An Indoor Scene Classification Method for Service Robot Based on CNN Feature by Shaopeng Liu, Guohui Tian

“…With the development of deep learning, fine-tuning CNN (Convolutional Neural Network) on target datasets has become a popular way to solve classification problems. …”
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Bearing fault diagnosis based on improved DenseNet for chemical equipment by Wu Huiyong, Jiang Kuan, Wang Yanyu

“…The alternating stacking strategy of channel and spatial attention further improves the feature extraction ability at different scales. This optimized structure increases the diversity and discriminative power of feature representations, enhancing the model’s performance in fault diagnosis tasks. …”
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Cross-ViT based benign and malignant classification of pulmonary nodules. by Qinfang Zhu, Liangyan Fei

“…The network first extracts different features independently through two branches and then performs feature fusion through the Cross fusion attention module. …”
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Grouped multi-scale vision transformer for medical image segmentation by Zexuan Ji, Zheng Chen, Xiao Ma

“…While early approaches based on Convolutional Neural Networks (CNNs) have achieved significant success, their limited receptive field constrains their ability to capture long-range dependencies. …”
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Advanced heart disease classification based on multi-channel heart sound coupling features. by Yu Fang, Dongbo Liu, Zijian Guo, Hongxia Leng, Xing Liu, Xiaochen Wu

“…Conventional heart sound classification methods often rely on single-channel, one-dimensional feature extraction, which inadequately captures pathological relationships across different auscultation zones, thereby limiting the accuracy of heart disease detection. …”
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Federated Learning for Brain Tumor Diagnosis: Methods, Challenges and Future Prospects by Ma Yuhan

“…Although these factors limit the widespread application of FL in medical settings, this paper also proposes potential solutions, such as improving algorithm interpretability through interpretable tools, and utilizing transfer learning and domain adaptation methods to enhance model effectiveness across different datasets. Techniques like knowledge distillation, model quantization, and pruning are proposed to enhance computational efficiency and minimize communication costs. …”
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Design and Analysis of an Expert System for the Detection and Recognition of Criminal Faces by Rishi Gupta, Amit Kumar Gupta, Deepak Panwar, Ashish Jain, Partha Chakraborty

“…In this study, they were analyzed and compared with the many methods of face detection and face recognition, such as HAAR cascades, local binary patterns histogram, support vector machines, convolutional neural networks, and ResNet-34. These methods include a variety of different approaches to recognizing faces. …”
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AI-Driven Non-Invasive Diagnosis of Diverse Medical Conditions Through Nail Image Analysis with High-Performance Ensemble Classifier by Abeer Alshiha, Wai Woo

“…The aim was to establish a non-invasive, automatic diagnosis tool for different nail conditions, utilizing deep convolutional neural networks (CNNs) for feature extraction. …”
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