A White Dwarf Catalog from LAMOST DR11 Using Deep Learning by Shengwen Zhang, Yanxia Zhang, Chao Liu

“…It involves the development of convolutional neural networks for processing 1D spectral data, alongside residual neural networks for handling 2D spectral images. …”
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Integrating deep learning and transfer learning: optimizing white blood cells classification in medical educational institutions by M. Hussein, Faten Abd El-Sattar Zahran El-Mougi

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Extended aerosol optical depth (AOD) time series analysis in an Alpine valley: a comparative study from 2007 to 2023 by J. Wagner, A. A. Ubele, V. Schenzinger, A. Kreuter, A. Kreuter

“…The Davos Station is part of the AErosol Robotic NETwork (AERONET), a global network providing high-quality, ground-based remote sensing aerosol data, and complies with the relevant requirements. …”
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Zastosowanie analizy wideo w zdalnym nauczaniu fizyki by Ihor Chernetskyi, Iryna Slipukhina, Fabian Andruszkiewicz

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Evaluating the Potential of SDGSAT-1 Glimmer Imagery for Urban Road Detection by Yu Wang, Hailan Huang, Bin Wu

“…Approximately, 64% of urban roads were detectable within the SDGSAT-1 glimmer imager data. Our study suggests that the SDGSAT-1 glimmer data have great potential for extracting urban roads.…”
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Physical Self-Esteem in Teenagers that Use Personal Photos as an Avatar in Their Social Net Profiles by Maksim S. Lytkin, Anastasia V. Miklyaeva

“…The article features the physical self-esteem in teenagers who use different types of avatars in social networks. The empirical data were collected by using questionnaire methods, which involved the modified Dembo-Rubinstein scale, A. …”
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A scenario-based analysis of wetlands as nature-based solutions for flood risk mitigation using the TELEMAC-2D model by Kirk B. Enu, Fabian Merk, Hao Su, Manuel Rauch, Aude Zingraff-Hamed, Karl Broich, Kristian Förster, Stephan Pauleit, Markus Disse

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Mitigating Polarization Leakage in Gas Pixel Detectors through Hybrid Machine Learning and Analytic Event Reconstruction by Nicoló Cibrario, Michela Negro, Raffaella Bonino, Nikita Moriakov, Luca Baldini, Niccoló Di Lalla, Alessandro Di Marco, Sergio Fabiani, Andrea Frassá, Alessio Gorgi, Fabio La Monaca, Luca Latronico, Simone Maldera, Alberto Manfreda, Fabio Muleri, Nicola Omodei, John Rankin, Carmelo Sgró, Stefano Silvestri, Paolo Soffitta, Stefano Tugliani

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Towards edge-collaborative, lightweight and privacy-preserving classification framework by Jinbo XIONG, Yongjie ZHOU, Renwan BI, Liang WAN, Youliang TIAN

“…Aiming at the problems of data leakage of perceptual image and computational inefficiency of privacy-preserving classification framework in edge-side computing environment, a lightweight and privacy-preserving classification framework (PPCF) was proposed to supports encryption feature extraction and classification, and achieve the goal of data transmission and computing security under the collaborative classification process of edge nodes.Firstly, a series of secure computing protocols were designed based on additive secret sharing.Furthermore, two non-collusive edge servers were used to perform secure convolution, secure batch normalization, secure activation, secure pooling and other deep neural network computing layers to realize PPCF.Theoretical and security analysis indicate that PPCF has excellent accuracy and proved to be security.Actual performance evaluation show that PPCF can achieve the same classification accuracy as plaintext environment.At the same time, compared with homomorphic encryption and multi-round iterative calculation schemes, PPCF has obvious advantages in terms of computational cost and communication overhead.…”
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Application of deep learning for diagnosis of shoulder diseases in older adults: a narrative review by Sung Min Rhee

“…This narrative review explores how deep learning (DL) can address diagnostic challenges by automating tasks such as image segmentation, disease detection, and motion analysis. …”
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Detection and segmentation framework for defect detection on multi-layer ceramic capacitors by Hyun-Jae Kim, Sung-Bin Son, Heung-Seon Oh

“…Furthermore, we generated pseudo-defect images using generative adversarial networks to obtain sufficient training data. …”
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Origin and Variety Identification of Dried Kelp Based on Fluorescence Fingerprinting and Machine Learning Approaches by Kana Suzuki, Rikuto Akiyama, Yvan Llave, Takashi Matsumoto

“…In addition, genetically close varieties have almost no differences in their base sequences; therefore, the accuracy of conventional identification methods using genetic analysis is limited. This study aimed to develop a system for identifying the origin and variety of dried kelp using fluorescence fingerprint data obtained by fluorescence spectroscopy and a convolutional neural network (CNN). …”
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Extraction of typical oyster pile columns in the Maowei Sea, Beibu Gulf, based on unmanned aerial vehicle laser point cloud orthophotos by Jinze Du, Jinze Du, Meiqin Huang, Zhenjun Kang, Zhenjun Kang, Zhenjun Kang, Yichao Tian, Yichao Tian, Yichao Tian, Jin Tao, Jin Tao, Qiang Zhang, Qiang Zhang, Yutong Xie, Yutong Xie, Yutong Xie, Jinying Mo, Jinying Mo, LiYan Huang, LiYan Huang, Yusheng Feng, Yusheng Feng

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Multi-Modal Dynamic Fusion for Defect Detection in Electronic Products: A Novel Approach Based on Energy and Deep Learning by Yulin Liu, Yang Gao

“…Specifically, Transformer architectures are employed for sensor data analysis, Convolutional Neural Networks (CNNs) are applied to process image data, and Multi-Layer Perceptrons (MLPs) are used to represent part-level features. …”
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Artificial intelligence: basic terms and concepts, the application in healthcare and clinical medicine by A. I. Lamotkin, D. I. Korabelnikov, I. A. Lamotkin

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AnVILWorkflow: A runnable workflow package for Cloud-implemented bioinformatics analysis pipelines [version 1; peer review: 2 approved] by Sean Davis, Marcel Ramos, Michael C. Schatz, Kai Gravel-Pucillo, Levi Waldron, Sehyun Oh, Martin Morgan, Vincent Carey

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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

“…The rapid development of unmanned aerial vehicles (UAVs) and imaging technologies has opened new research avenues for precision agriculture, particularly in the context of plant phenotyping where their utilization has been intensive over the last decade. …”
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Automated Detection of Recent Mud Extrusions Using UAV Imagery and Deep Learning: A Comparative Analysis of Traditional and CNN-Based Approaches by M. Guastella, M. Guastella, A. Pisciotta, R. Martorana, A. D’Alessandro

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Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

“…These studies collectively demonstrate the potential of radiomics-based machine learning models in accurately distinguishing between glioma subtypes and grades. Various imaging modalities, including MRI, PET/CT, and advanced techniques like ASL and DTI, were utilized to extract radiomic features for analysis. …”
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Refining Intra-Arterial Therapy Selection for Large Hepatocellular Carcinoma: A Deep Learning Approach Based on Covariate Interaction Analysis by An C, Li L, Luo Y, Zuo M, Liu W, Li C, Wu P

“…The DEep Learning for Interaction and Covariate Analysis in Intra-arterial Therapy SElection (DELICAITE) model integrates deep convolutional neural networks (DCNN) with covariate interaction analysis. …”
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