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07/05/2023
ChiENN: Embracing Molecular Chirality with Graph Neural Networks
Graph Neural Networks (GNNs) play a fundamental role in many deep learni...
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11/28/2021
Imbalanced data preprocessing techniques utilizing local data characteristics
Data imbalance, that is the disproportion between the number of training...
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05/09/2021
DiagSet: a dataset for prostate cancer histopathological image classification
Cancer diseases constitute one of the most significant societal challeng...
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05/09/2021
RB-CCR: Radial-Based Combined Cleaning and Resampling algorithm for imbalanced data classification
Real-world classification domains, such as medicine, health and safety, ...
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04/17/2021
Potential Anchoring for imbalanced data classification
Data imbalance remains one of the factors negatively affecting the perfo...
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04/07/2020
CSMOUTE: Combined Synthetic Oversampling and Undersampling Technique for Imbalanced Data Classification
In this paper we propose two novel data-level algorithms for handling da...
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04/07/2020
Combined Cleaning and Resampling Algorithm for Multi-Class Imbalanced Data with Label Noise
The imbalanced data classification is one of the most crucial tasks faci...
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04/07/2020
Two-Stage Resampling for Convolutional Neural Network Training in the Imbalanced Colorectal Cancer Image Classification
Data imbalance remains one of the open challenges in the contemporary ma...
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06/02/2019