Results 41 to 50 of about 39,918 (213)
Yielding Multi-Fold Training Strategy for Image Classification of Imbalanced Weeds
Applied Sciences, 2021 An imbalanced dataset is a significant challenge when training a deep neural network (DNN) model for deep learning problems, such as weeds classification.
Vo Hoang Trong +3 more
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Adversarial Pairwise Reverse Attention for Camera Performance Imbalance in Person Re-identification: New Dataset and Metrics [PDF]
, 2022 Eugene P.W. Ang +4 more
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Adaptive Age Estimation towards Imbalanced Datasets
Applied Sciences, 2023 Current age estimation datasets often have a skewed long-tail distribution with significant data imbalance, rather than an ideal uniform distribution for each category. The existing age estimation algorithms that rely on label distribution do not leverage data density information to address the issue of data imbalance.
Zhiang Dong, Xiaoqiang Li
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Sensors, 2022 In order to solve the problem of imbalanced and noisy data samples for the fault diagnosis of rolling bearings, a novel ensemble capsule network (Capsnet) with a convolutional block attention module (CBAM) that is based on a weighted majority voting ...
Zengbing Xu +3 more
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Solving Simulated Imbalanced Body Performance Data using A-SUWO and Tomek Link Algorithm
Journal of Applied Engineering and Technological ScienceThis research examines the impact of various sampling techniques on the performance of classification models in the context of imbalanced datasets, employing the body performance dataset as a case study. Many studies in this field analyze the effect of
Febryan Grady +2 more
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An Imbalanced R-STDP Learning Rule in Spiking Neural Networks for Medical Image Classification
IEEE Access, 2020 Spiking neural networks (SNNs) have the advantages of inherent power-efficiency, biological plausibility and good image recognition performance. They are good candidates for medical image classification especially when the labeled training data are ...
Qian Zhou, Cong Ren, Saibing Qi
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Three-Stage Recursive Learning Technique for Face Mask Detection on Imbalanced Datasets
MathematicsIn response to the COVID-19 pandemic, governments worldwide have implemented mandatory face mask regulations in crowded public spaces, making the development of automatic face mask detection systems critical.
Chi-Yi Tsai +2 more
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Current Directions in Biomedical Engineering, 2023 The AUC margin loss is a valuable loss function for medical image classification as it addresses the problems of imbalanced and noisy labels. It is used by the current winner of the CheXpert competition.
Ihler Sontje, Kuhnke Felix
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An in-depth performance analysis of the oversampling techniques for high-class imbalanced dataset [PDF]
, 2021 Prasetyo Adi Wibowo, Chastine Fatichah
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On the Classification of Imbalanced Datasets
International Journal of Computer Applications, 2012 In recent research the classifications of imbalanced data sets have received considerable attention. It is natural that due to the class imbalance the classifier tends to favour majority class. In this paper we investigate the performance of different methods for handling data imbalance in the microcalcification classification which is a classical ...
H. S. Sheshadri, Arun KumarM.N
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