Bridging communication gaps between hearing and hearing-impaired individuals is an important challenge in assistive ...

1 Peter the Great St. Petersburg Polytechnic University, Saint Petersburg, Russia 2 All-Russian Institute of Plant Protection, Saint Petersburg, Russia However, despite rapid methodological advances, ...

Research in self-supervised learning (SSL) with natural images has progressed rapidly in recent years and is now increasingly being applied to and benchmarked with datasets containing remotely sensed ...

Some format handlers modify input text (e.g., encoding fixes, page joins), but line numbers used for insights are computed before normalization. This causes mismatches between reported lines and ...

Abstract: Optimizing machine learning (ML) model performance relies heavily on appropriate data preprocessing techniques. Despite the widespread use of standardization and normalization, empirical ...

Be honest, when was the last time you had your blood pressure checked? No, really? The health marker is something many of us gloss over, and it's easy to skim through the years completely unaware of ...

While preprocessing the Brats2023 dataset using nnU-Net with the command nnUNet_plan_and_preprocess -t 180 --verify_dataset_integrity, the process successfully validates the training and test sets and ...

Abstract: According to the World Health Organization (WHO), some chronic diseases such as diabetes mellitus, stroke, cancer, cardiac vascular, kidney failure, and hypertension are essential for early ...

Introduction: Registration to a standardized template (i.e. “normalization”) is a critical step when performing neuroimaging studies. We present a comparative study involving the evaluation of general ...

(Left) Current dimensionality reduction methods for scRNA-seq data involve conventional data preprocessing steps, such as log normalization, followed by manual selection of signals from the scaled ...