Online Learning under Haphazard Input Conditions: A Comprehensive Review and Analysis

R Agarwal, A Das, A Horsch, K Agarwal… - arXiv preprint arXiv …, 2024 - arxiv.org
The domain of online learning has experienced multifaceted expansion owing to its
prevalence in real-life applications. Nonetheless, this progression operates under the …

Hybrid workflow of Simulation and Deep Learning on HPC: A Case Study for Material Behavior Determination

L Zhong, D Hoppe, N Zhou… - 2021 IEEE International …, 2021 - ieeexplore.ieee.org
Nowadays, machine learning (ML), especially deep learning (DL) methods, provide ever
more real-life solutions. However, the lack of training data is often a crucial issue for these …

Artefact removal in ground truth deficient fluctuations-based nanoscopy images using deep learning

S Jadhav, S Acuña, IS Opstad… - Biomedical Optics …, 2020 - opg.optica.org
Image denoising or artefact removal using deep learning is possible in the availability of
supervised training dataset acquired in real experiments or synthesized using known noise …

Review of cell image synthesis for image processing

V Ulman, D Wiesner - Biomedical Image Synthesis and Simulation, 2022 - Elsevier
Opposites attract, also in the biomedical field and during the processing of cell microscopy
images. In the same spirit, image processing, the indispensable analyst tool, is often …

Morphology-Based Machine Learning Mechanism for Unsupervised Framework Prediction Using Statistical Segmentation on Blood Cancer

MP Ishavarbhai, AK Sharma, M Patel… - … Conference on Advances …, 2024 - Springer
Leukaemia is a disease that is related to cancerous cells. It is also lethal, and people of all
age groups can be affected by it. WBCs especially affect this, and they are followed by a …