RNA secondary structure prediction by conducting multi-class classifications by Jiyuan Yang, Kengo Sato, Martin Loza, Sung-Joon Park, Kenta Nakai

“…In this study, we propose a simple method by considering RNA secondary structure prediction as multiple multi-class classifications, which eliminates the need for those complicated post-processing steps. Then, we use this method to train and evaluate our model based on the attention mechanism and the convolutional neural network. …”
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Post marketing safety assessment of the novel postpartum depression drug, Zuranolone: evidence from real-world pharmacovigilance analysis based on the FDA adverse event reporting s... by Duoqin Huang, Zixin Luo, Xi Gong, Kang Zou, Yu Peng, Shaoying Zeng

“…The Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Convolutional Probabilistic Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS) were used collectively to detect risk signals.ResultsThis study identified 154 reports primarily suspecting Zuranolone and 426 adverse drug events from a total of 1,626,204 adverse event (AE) reports. …”
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DamageScope: An Integrated Pipeline for Building Damage Segmentation, Geospatial Mapping, and Interactive Web-Based Visualization by Sultan Al Shafian, Chao He, Da Hu

“…This study introduces DamageScope, an integrated deep learning framework designed to detect and classify building damage levels from post-disaster satellite imagery. The proposed system leverages a convolutional neural network trained exclusively on post-event data to segment building footprints and assign them to one of four standardized damage categories: no damage, minor damage, major damage, and destroyed. …”
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High-Quality Damaged Building Instance Segmentation Based on Improved Mask Transfiner Using Post-Earthquake UAS Imagery: A Case Study of the Luding Ms 6.8 Earthquake in China by Kangsan Yu, Shumin Wang, Yitong Wang, Ziying Gu

“…This method primarily employed deformable convolution in the backbone network to enhance adaptability to collapsed buildings of arbitrary shapes. …”
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iKcr-DRC: prediction of lysine crotonylation sites in proteins based on a novel attention module and DenseNet by Xin Wei, Xin Wei, Xin Wei, Siqin Hu, Jian Tu, Muhammad Akmal Remli, Muhammad Akmal Remli

“…The model leverages a densely connected convolutional network (DenseNet) as its backbone to effectively capture high-level local features from protein sequences. …”
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Comparison of Surgical Outcomes between Endovenous Laser Ablation and Conventional Surgery in Patients with Lower Limb Varicose Veins: A Prospective Interventional Study by Mannam Viswateja, Deepak R Chavan, Vijaya Patil, Vikram U Sindagikar

“…Introduction: Dilated, convoluted, subcutaneous veins measuring more than 3 mm in diameter when measured while upright and exhibiting reflux are called varicose veins. …”
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PIABC: Point Spread Function Interpolative Aberration Correction by Chanhyeong Cho, Chanyoung Kim, Sanghoon Sull

“…We compare our method—based on pixel-wise, physical correction, and densely interpolated PSF at pre-processing—with post-processing networks, including deformable convolutional neural networks (CNNs) that enhance image quality without modeling degradation. …”
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Deep learning approach for automated ‘Kent’ mango maturity grading in compliance with Peruvian standards by Orlando Salazar-Campos, Javier Moran Ruiz, José Luis Peralta, Mirian Rubio Cieza, Breysi Salazar Medina, Johonathan Salazar-Campos

“…Deep learning, particularly convolutional neural networks (CNNs), has significantly advanced automated fruit classification based on image analysis. …”
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Optimal, fast, and robust inference of reionization-era cosmology with the 21cmPIE-INN by Benedikt Schosser, Caroline Heneka, Tilman Plehn

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Identifying the quantum properties of hadronic resonances using machine learning by Jakub Filipek, Shih-Chieh Hsu, John Kruper, Kirtimaan Mohan, Benjamin Nachman

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Scattering from an external field in quantum chromodynamics at high energies: From foundations to interdisciplinary connections by Athanasia-Konstantina Angelopoulou, Anh Dung Le, Stéphane Munier

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SDA-Mask R-CNN: An Advanced Seabed Feature Extraction Network for UUV by Yao Xiao, Dongchen Dai, Hongjian Wang, Chengfeng Li, Shaozheng Song

“…First, we introduce a Structural Synergistic Group-Attention Residual Network (SSGAR-Net) that integrates group convolution with an enhanced convolutional block attention mechanism, complemented by a layer-skipping architecture for optimized information flow and redundancy verification for computational efficiency. …”
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DLAFNet: Direct LiDAR-Aerial Fusion Network for Semantic Segmentation of 2-D Aerial Image and 3-D LiDAR Point Cloud by Wei Liu, He Wang, Yicheng Qiao, Haopeng Zhang, Junli Yang

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ECO++: Adaptive deep feature fusion target tracking method in complex scene by Yuhan Liu, He Yan, Qilie Liu, Wei Zhang, Junbin Huang

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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

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Inclusion Relation between Various Subclasses of Harmonic Univalent Functions Associated with Wright’s Generalized Hypergeometric Functions by Rajavadivelu Themangani, Saurabh Porwal, Nanjundan Magesh

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A deep learning short-term traffic flow prediction method considering spatial-temporal association by Yang ZHANG, Yue HU, Dongrong XIN

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Enhancing CNN-Based Signal Denoising: A Novel Metric Framework With Harmonic Suppression Through Hybrid Modeling by Omer Nacar, Turgay Koc

“…Convolutional neural networks (CNNs) show promise for signal denoising but can introduce harmonic distortions due to their nonlinearity. …”
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UAVAI-YOLO: dense small target detection algorithm based on UAV aerial images by HE Zhiqian, CAO Lijie

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Foreign object detection on coal conveyor belt enhanced by attention mechanism by ZHANG Yang, CHENG Zhiyu, CHEN Yunjiang, ZHANG Jiannan, YUAN Wensheng, ZHANG Hui

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