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Found 10 papers, 5 papers with code
Annotating Ambiguous Images: General Annotation Strategy for High-Quality Data with Real-World Biomedical Validation
In the field of image classification, existing methods often struggle with biased or ambiguous data, a prevalent issue in real-world scenarios.
Label Smarter, Not Harder: CleverLabel for Faster Annotation of Ambiguous Image Classification with Higher Quality
High-quality data is crucial for the success of machine learning, but labeling large datasets is often a time-consuming and costly process.
GADformer: A Transparent Transformer Model for Group Anomaly Detection on Trajectories
Hence, this paper introduces GADformer, a BERT-based model for attention-driven GAD on trajectories in unsupervised and semi-supervised settings.
Automated Classification of Nanoparticles with Various Ultrastructures and Sizes
Accurately measuring the size, morphology, and structure of nanoparticles is very important, because they are strongly dependent on their properties for many applications.
Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation
We propose a data-centric image classification benchmark with ten real-world datasets and multiple annotations per image to allow researchers to investigate and quantify the impact of such data quality issues.
S2C2 - An orthogonal method for Semi-Supervised Learning on ambiguous labels
Semi-Supervised Learning (SSL) can decrease the required amount of labeled image data and thus the cost for deep learning.
Learning Stixel-based Instance Segmentation
Stixels have been successfully applied to a wide range of vision tasks in autonomous driving, recently including instance segmentation.
A data-centric approach for improving ambiguous labels with combined semi-supervised classification and clustering
In our data-centric approach, we propose a method to relabel such ambiguous labels instead of implementing the handling of this issue in a neural network.
2D and 3D Segmentation of uncertain local collagen fiber orientations in SHG microscopy
Furthermore, we compare a variety of 2D and 3D methods such as classical approaches like Fourier analysis with state-of-the-art deep neural networks for the classification of local fiber orientations.
Restoration of Images with Wavefront Aberrations
In most coherent imaging systems, especially in astronomy, the wavefront deformation is known.
