Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

“…To deal with the issue of unbalanced classes in the TB CXR dataset, we use different oversampling techniques such as weighted averaging, SMOTE, ADASYN and Borderline SMOTE. …”
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YOLO-SWD—An Improved Ship Recognition Algorithm for Feature Occlusion Scenarios by Ruyan Zhou, Mingkang Gu, Haiyan Pan

“…YOLOv11 possesses stronger feature extraction capabilities and its multi-branch structure effectively captures features of targets at different scales. Three improved modules are introduced: the DLKA module enhances the perception of local details and global context through dynamic deformable convolution and large receptive field attention mechanisms; the CKSP module improves the model’s ability to extract target boundaries and shapes; and the WTHead enhances the diversity and robustness of feature extraction. …”
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SuperEdgeGO: Edge-supervised graph representation learning for enhanced protein function prediction. by Shugang Zhang, Yuntong Li, Wenjian Ma, Qing Cai, Jing Qin, Xiangpeng Bi, Huasen Jiang, Xiaoyu Huang, Zhiqiang Wei

“…In this article, we propose SuperEdgeGO, which introduces the supervision of edges in protein graphs to learn a better graph representation for protein function prediction. Different from common graph convolution methods that uses edge information in a plain or unsupervised way, we introduce a supervised attention to encode the residue contacts explicitly into the protein representation. …”
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SiamAHG: adaptive hierarchical graph attention for lightweight siamese tracking by Na Li, Yaofu Fan, Xuhao Chen, Xinyu Liu, Jinglu He

“…AFMRM refines feature maps of different stages and strengthens the model expression by combining multiple convolutional kernels dynamically based upon diverse attentions. …”
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Generalizable deep learning models for predicting laboratory earthquakes by Chonglang Wang, Kaiwen Xia, Wei Yao, Chris Marone

“…Here, we show a fine-tuned convolutional neural network (CNN) model effectively transfer across different conditions. …”
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Prediction of foreign currency exchange rates using an attention-based long short-term memory network by Shahram Ghahremani, Uyen Trang Nguyen

“…We conducted comprehensive experiments to evaluate and compare the performance of ALFA against several models used in previous work and against state-of-the-art deep learning models such as temporal convolutional networks (TCN) and Transformer. Experimental results show that ALFA outperforms the baseline models in most cases, across different currency pairs and feature sets, thanks to its attention mechanism that filters out irrelevant or redundant data to focus on important features. …”
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An automated deep learning model for liver tumor and skin lesion segmentation by R. V. Manjunath, N. Yashaswini Gowda, Manjunath Lakkannavar

“…Abstract Artificial Intelligence plays a vital role in automatically identifying different diseases from a given set of medical images. …”
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Learning Feature Fusion in Deep Learning-Based Object Detector by Ehtesham Hassan, Yasser Khalil, Imtiaz Ahmad

“…Deep features characterize different regions of interest in a testing image with a rich set of statistical features. …”
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SMS Spam Detection System Based on Deep Learning Architectures for Turkish and English Messages by Hakan Can Altunay, Zafer Albayrak

“…Short Message Service (SMS) still continues its existence despite the emergence of different messaging services. It plays a part in our lives as a communication service. …”
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Pipeline and Rotating Pump Condition Monitoring Based on Sound Vibration Feature-Level Fusion by Yu Wan, Shaochen Lin, Yan Gao

“…Moreover, a convolutional neural network (CNN)-derived feature set is established based on a one-dimensional CNN (1D CNN). …”
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Load magnitude and location estimation on additively manufactured circular structures using deep learning by Romaine Byfield, Ibrahim Tansel

“…Two 3D printed stainless steel rocket nozzle type structures with two different sizes and a C shaped tube section were used. …”
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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

“…Intelligent heart sound diagnosis based on Convolutional Neural Networks (CNN) has been attracting increasing attention due to its accuracy and efficiency, which have been improved by recent studies. …”
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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 advantages of feature extraction by a convolutional neural network and the high efficiency of a hash index structure in retrieval are used to solve the shortcomings of traditional methods in terms of accuracy and other aspects in image retrieval. …”
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Multi-Scale DCNN with Dynamic Weight and Part Cross-Entropy Loss for Skin Lesion Diagnosis by Gaoshuai Wang, Linrunjia Liu, Fabrice Lauri, Amir HAJJAM El Hassani

“…Although present methods often use the multi-branch structure to get more clues, the rigescent methods of cropping zone and fusing branch results fail to handle the instability of the disease zone and the difference in branch results, which leads to improper cropping and degrades Deep Convolutional Neural Networks (DCNN)’s performance. …”
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