Výsledky vyhľadávania - convolutional denoising autoencoder (dane)~

A deep learning approach to prediction of blood group antigens from genomic data.

Autori: Moslemi, Camous Sækmose, Susanne Larsen, Rune a ďalší

Zdroj: Transfusion; Nov2024, Vol. 64 Issue 11, p2179-2195, 17p

Predmety: BLOOD group antigens, CONVOLUTIONAL neural networks, BLOOD grouping & crossmatching, BLOOD groups, DEEP learning

Deep Learning Techniques for Prostate Cancer Analysis and Detection: Survey of the State of the Art.

Autori: Olawuyi, Olushola Viriri, Serestina

Zdroj: Journal of Imaging; Aug2025, Vol. 11 Issue 8, p254, 36p

Single-cell omics: experimental workflow, data analyses and applications.

Autori: Sun F Li H Sun D a ďalší

Zdroj: Science China. Life sciences [Sci China Life Sci] 2025 Jan; Vol. 68 (1), pp. 5-102. Date of Electronic Publication: 2024 Jul 23.

Spôsob vydávania: Journal Article; Review

Informácie o časopise: Publisher: Science China Press, co-published with Springer Country of Publication: China NLM ID: 101529880 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1869-1889 (Electronic) Linking ISSN: 16747305 NLM ISO Abbreviation: Sci China Life Sci Subsets: MEDLINE

Výrazy zo slovníka MeSH: Single-Cell Analysis*/methods , Workflow*, Humans ; Genomics/methods ; Animals ; Data Analysis ; Proteomics/methods ; Metabolomics/methods

融合节点属性和无环路径的社交网络嵌入方法. (Chinese)

Alternate Title: Social Network Embedding Method Combining Node Attributes and Loop-Free Path. (English)

Autori: 王本钰 顾益军 彭舒凡

Zdroj: Journal of Frontiers of Computer Science & Technology; Nov2022, Vol. 16 Issue 11, p2505-2518, 14p

Predmety: SOCIAL networks, VIRTUAL networks, TASK analysis, NETWORK performance, SOCIAL structure, PROBLEM solving

Multispectral Plant Disease Detection with Vision Transformer–Convolutional Neural Network Hybrid Approaches.

Autori: De Silva, Malithi Brown, Dane

Zdroj: Sensors (14248220); Oct2023, Vol. 23 Issue 20, p8531, 22p

Predmety: DEEP learning, MACHINE learning, TRANSFORMER models, CONVOLUTIONAL neural networks, AGRICULTURE, PLANT identification

Interpretable Deep Learning for Diabetic Retinopathy: A Comparative Study of CNN, ViT, and Hybrid Architectures.

Autori: Zhang, Weijie Belcheva, Veronika Ermakova, Tatiana

Zdroj: Computers (2073-431X); May2025, Vol. 14 Issue 5, p187, 24p

Predmety: TRANSFORMER models, CONVOLUTIONAL neural networks, VISION disorders, DIABETIC retinopathy, COMPUTER-assisted image analysis (Medicine), DEEP learning

Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review.

Autori: Lubbad, M. Karaboga, D. Basturk, A. a ďalší

Zdroj: Neural Computing & Applications; Apr2024, Vol. 36 Issue 12, p6355-6379, 25p

Predmety: DEEP learning, MACHINE learning, CANCER diagnosis, CONVOLUTIONAL neural networks, RENAL cell carcinoma, ARTIFICIAL intelligence

Comprehensive review of recent developments in visual object detection based on deep learning.

Autori: Edozie, Enerst Shuaibu, Aliyu Nuhu John, Ukagwu Kelechi a ďalší

Zdroj: Artificial Intelligence Review; Sep2025, Vol. 58 Issue 9, p1-97, 97p

Generative AI for Intelligent Transportation Systems: Road Transportation Perspective.

Autori: Yan, Huan Li, Yong

Zdroj: ACM Computing Surveys; Dec2025, Vol. 57 Issue 12, p1-45, 45p

Design and sustainability of polypeptide material systems.

Autori: Yorke, Sarah K. Yang, Zhenze Wiita, Elizabeth G. a ďalší

Zdroj: Nature Reviews Materials; Oct2025, Vol. 10 Issue 10, p750-768, 19p

Multi-head de-noising autoencoder-based multi-task model for fault diagnosis of rolling element bearings under various speed conditions.

Autori: Jongmin Park Jinoh Yoo Taehyung Kim a ďalší

Zdroj: Journal of Computational Design & Engineering; Aug2023, Vol. 10 Issue 4, p1804-1820, 17p

Predmety: ROLLER bearings, FAULT diagnosis, LEARNING strategies

Current State of the Art and Potential for Construction and Demolition Waste Processing: A Scoping Review of Sensor-Based Quality Monitoring and Control for In- and Online Implementation in Production Processes.

Autori: Göbbels, Lieve Feil, Alexander Raulf, Karoline a ďalší

Zdroj: Sensors (14248220); Jul2025, Vol. 25 Issue 14, p4401, 38p

Predmety: CONSTRUCTION & demolition debris, QUALITY assurance, REAL-time computing, SUSTAINABLE construction, DETECTORS, SPECTROMETRY, IMAGING systems

Deep Learning–accelerated MRI in Body and Chest.

Autori: Rajamohan, Naveen Bagga, Barun Bansal, Bhavik a ďalší

Zdroj: Journal of Computer Assisted Tomography; Jul/Aug2025, Vol. 49 Issue 4, p531-544, 14p

Benchmark Tests of Atom Segmentation Deep Learning Models with a Consistent Dataset.

Autori: Wei, Jingrui Blaiszik, Ben Scourtas, Aristana a ďalší

Zdroj: Microscopy & Microanalysis; Apr2023, Vol. 29 Issue 2, p552-562, 11p

DNA sequence analysis landscape: a comprehensive review of DNA sequence analysis task types, databases, datasets, word embedding methods, and language models.

Autori: Asim, Muhammad Nabeel Ibrahim, Muhammad Ali Zaib, Arooj a ďalší

Zdroj: Frontiers in Medicine; 2025, p1-64, 64p

Listening for Sirens: Locating and Classifying Acoustic Alarms in City Scenes.

Autori: Marchegiani, Letizia Newman, Paul

Zdroj: IEEE Transactions on Intelligent Transportation Systems; Oct2022, Vol. 23 Issue 10, p17087-17096, 10p

Transitioning from wet lab to artificial intelligence: a systematic review of AI predictors in CRISPR.

Autori: Abbasi, Ahtisham Fazeel Asim, Muhammad Nabeel Dengel, Andreas

Zdroj: Journal of Translational Medicine; 2/4/2025, Vol. 23 Issue 1, p1-46, 46p

Predmety: GENOME editing, ARTIFICIAL intelligence, CRISPRS, MACHINE learning, DEEP learning

Deep Learning‐Based Multiomics Data Integration Methods for Biomedical Application.

Autori: Wen, Yuqi Zheng, Linyi Leng, Dongjin a ďalší

Zdroj: Advanced Intelligent Systems (2640-4567); May2023, Vol. 5 Issue 5, p1-15, 15p

Recommendation system using a deep learning and graph analysis approach.

Autori: Kherad, Mahdi Bidgoly, Amir Jalaly

Zdroj: Computational Intelligence; Oct2022, Vol. 38 Issue 5, p1859-1883, 25p

Predmety: RECOMMENDER systems, DEEP learning, INFORMATION filtering, TRUST, MATRIX decomposition, TELECOMMUNICATION systems

Geografický termín: LOUVAIN (Belgium)

Deep Attributed Network Embedding by Preserving Structure and Attribute Information.

Autori: Hong, Richang He, Yuan Wu, Le a ďalší

Zdroj: IEEE Transactions on Systems, Man & Cybernetics. Systems; Mar2021, Vol. 51 Issue 3, p1434-1445, 12p

Predmety: TASK analysis, DATA modeling, MACHINE learning, ROUTING algorithms