Transformation of Nonmultiple Cluster Music Cyclic Shift Topology to Music Performance Style by Jing Li

“…This paper proposes a performance style conversion network based on recurrent neural network and convolutional neural network. The bidirectional recurrent neural network based on Gated Recurrent Unit (GRU) is used to extract different styles of note feature vector sequences, and the extracted note feature vector sequence is used to predict the intensity of a specific style, and the intensity changes of different styles of nonmultiple cluster music are better learned. …”
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Handwritten Geez Digit Recognition Using Deep Learning by Mukerem Ali Nur, Mesfin Abebe, Rajesh Sharma Rajendran

“…Convolutional neural network (CNN) is preferable for pattern recognition like in handwritten document recognition by extracting a feature from different styles of writing. …”
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Multibranch semantic image segmentation model based on edge optimization and category perception. by Zhuolin Yang, Zhen Cao, Jianfang Cao, Zhiqiang Chen, Cunhe Peng

“…In semantic image segmentation tasks, most methods fail to fully use the characteristics of different scales and levels but rather directly perform upsampling. …”
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Heart Sound Classification Based on Multi-Scale Feature Fusion and Channel Attention Module by Mingzhe Li, Zhaoming He, Hao Wang

“…In this paper, we propose a heart sound classification model named CAFusionNet, which fuses features from different layers with varying resolution ratios and receptive field sizes. …”
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The analysis of artificial intelligence knowledge graphs for online music learning platform under deep learning by Shen Jiang, Ningning Shi, Chang Liu

“…Experimental analysis based on different datasets shows that the proposed music recommendation platform performs well in multiple key performance indicators. …”
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Comparison of YOLOv5 for Classifying Mangrove Leaf Species using CNN-Based by Anindita Septiarini, Rita Diana, Rahmat Kamara, Novianti Puspitasari, Anton Prafanto

“…Although each type of mangrove plant has different characteristics, several types look similar, especially on the leaves. …”
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A Fault Identification Method of Mechanical Element Action Unit Based on CWT-2DCNN by Hongyu Ge, Yujiao Guo, Tianyu Luo, Manzhi Yang, Chuanwei Zhang

“…By using this method, the different fault types of mechanical element action units can be accurately identified, which has a certain application in the field of mechanical fault identification and diagnosis.…”
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Large-Scale Image Retrieval of Tourist Attractions Based on Multiple Linear Regression Equations by Yinping Song

“…The results show that compared with the above two algorithms, for most of the attractions, the method has a relatively obvious advantage in the accuracy of retrieval, and when there are few similar images of a particular attraction in the attraction image library, the accuracy of the query results is not much different from the first two methods.…”
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Multi-Scale Long- and Short-Range Structure Aggregation Learning for Low-Illumination Remote Sensing Imagery Enhancement by Yu Cao, Yuyuan Tian, Xiuqin Su, Meilin Xie, Wei Hao, Haitao Wang, Fan Wang

“…Profiting from the surprising non-linear expressive capacity, deep convolutional neural networks have inspired lots of progress in low illumination (LI) remote sensing image enhancement. …”
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Development of Robust CNN Architecture for Grading and Classification of Renal Cell Carcinoma Histology Images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Concatenating samples from three different parts of architecture allows for the encompassing of varied features, further improving grading and classification accuracy. …”
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LSTM and ResNet18 for optimized ambulance routing and traffic signal control in emergency situations by Madallah Alruwaili, Ali Ali, Mohammed Almutairi, Abdulaziz Alsahyan, Mahmood Mohamed

“…Abstract Traffic congestion, particularly in rapidly expanding urban centers, significantly impacts the timely delivery of emergency medical services (EMS), where every minute can mean the difference between life and death. Traditional traffic signal control systems often lack real-time adaptability to prioritize emergency vehicles, resulting in delays caused by congestion around ambulances. …”
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Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study by Xin He, Xiang-Hui Bai, Hui Chen, Wei-Wei Feng

“…There was a statistically significant difference between the Vision Transformer and SA, and between the Vision Transformer and Swin Transformer models (AUC: 0.87 vs. 0.97, P = 0.01; AUC: 0.87 vs. 0.92, P = 0.04). …”
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An extensive experimental analysis for heart disease prediction using artificial intelligence techniques by D. Rohan, G. Pradeep Reddy, Y. V. Pavan Kumar, K. Purna Prakash, Ch. Pradeep Reddy

“…The feature selection techniques considered for the research are Information Gain, Chi-Square Test, Fisher Discriminant Analysis (FDA), Variance Threshold, Mean Absolute Difference (MAD), Dispersion Ratio, Relief, LASSO, Random Forest Importance, Linear Discriminant Analysis (LDA), and Principal Component Analysis (PCA). …”
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Identifying native grasslands and key phenological stages using time series Sentinel-2 data and deep learning models by Yihan Pu, Amy Nixon, Beatriz Prieto, Xulin Guo

“…This study aims to identify native grasslands in the Mixed Grasslands ecoregion of Saskatchewan using Sentinel-2 Normalized Difference Vegetation Index (NDVI) time series data through deep learning and multi-temporal approaches. …”
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A Novel Foundation Model-Based Framework for Multimodal Retinal Age Prediction by Christopher Nielsen, Matthias Wilms, Nils D. Forkert

“…The retinal age gap (RAG; the difference between the retina’s biological and chronological age) has recently gained increased attention as a potential image-based, non-invasive, and accessible biomarker for a broad spectrum of ocular and non-ocular diseases. …”
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A Practical Framework for Estimating Façade Opening Rates of Rural Buildings Using Real-Scene 3D Models Derived from Unmanned Aerial Vehicle Photogrammetry by Zhuangqun Niu, Ke Xi, Yifan Liao, Pengjie Tao, Tao Ke

“…Regarding the mean relative error (MRE), a critical evaluation metric which measures the relative difference between the estimated FOR and its ground truth, the proposed method outperforms the closest baseline by 5%. …”
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Deep Learning-Based Instance Segmentation of Galloping High-Speed Railway Overhead Contact System Conductors in Video Images by Xiaotong Yao, Huayu Yuan, Shanpeng Zhao, Wei Tian, Dongzhao Han, Xiaoping Li, Feng Wang, Sihua Wang

“…Consequently, segmentation outcomes from neighboring frames are utilized, and mask-difference analysis is performed to autonomously detect conductor galloping locations, emphasizing their contours for the clear depiction of galloping characteristics. …”
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INFORMATION TECHNOLOGY FOR RECOGNITION OF ROAD SIGNS USING A NEURAL NETWORK by Elena Yashina, Roman Artiukh, Nikolai Рan, Andrei Zelensky

“…The process of interaction of the system with different data sources is represented by a diagram of precedents. …”
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Automated analysis of high‐content microscopy data with deep learning by Oren Z Kraus, Ben T Grys, Jimmy Ba, Yolanda Chong, Brendan J Frey, Charles Boone, Brenda J Andrews

“…We also demonstrate the ability of DeepLoc to classify highly divergent image sets, including images of pheromone‐arrested cells with abnormal cellular morphology, as well as images generated in different genetic backgrounds and in different laboratories. …”
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On the improvement of schizophrenia detection with optical coherence tomography data using deep neural networks and aggregation functions by Paweł Karczmarek, Małgorzata Plechawska-Wójcik, Adam Kiersztyn, Adam Domagała, Agnieszka Wolinska, Steven M. Silverstein, Kamil Jonak, Paweł Krukow

“…Among over 300, 000 different variants of tested aggregation operators, a few versions provided satisfactory results.…”
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