A survey of deep domain adaptation based on label set classification
M Fan, Z Cai, T Zhang, B Wang - Multimedia Tools and Applications, 2022 - Springer
Traditional machine learning requires good tags to obtain excellent performance, while
manual tagging usually consumes a lot of time and money. Due to the influence of domain …
manual tagging usually consumes a lot of time and money. Due to the influence of domain …
Robust fine-grained image classification with noisy labels
X Tan, Z Dong, H Zhao - The Visual Computer, 2023 - Springer
Since annotating fine-grained labels requires special expertise, label annotations often lack
quality for many real-world fine-grained image classifications (FGIC). Due to the …
quality for many real-world fine-grained image classifications (FGIC). Due to the …
Lightweight Deep Learning Model Optimization for Medical Image Analysis
Medical image labeling requires specialized knowledge; hence, the solution to the
challenge of medical image classification lies in efficiently utilizing the few labeled samples …
challenge of medical image classification lies in efficiently utilizing the few labeled samples …
A Progressive Deep Neural Network Training Method for Image Classification with Noisy Labels
X Yan, X **a, L Wang, Z Zhang - Applied Sciences, 2022 - mdpi.com
Deep neural networks (DNNs) require large amounts of labeled data for model training.
However, label noise is a common problem in datasets due to the difficulty of classification …
However, label noise is a common problem in datasets due to the difficulty of classification …
АНСАМБЛЬДІК ТӘСІЛ НЕГІЗІНДЕ КЕСКІНДІ ӨҢДЕУДІҢ ТИІМДІ АЛГОРИТМІН ҚҰРУ
Н Абдразакұлы, Л Черикбаева… - Известия НАН РК …, 2024 - journals.nauka-nanrk.kz
Аннотация По данным Всемирной организации здравоохранения, более 17 миллионов
человек во всем мире ежегодно умирают от болезней системы кровообращения …
человек во всем мире ежегодно умирают от болезней системы кровообращения …