Results 21 to 30 of about 46,171 (307)
Applied Sciences, 2021 Human activity recognition (HAR) is the study of the identification of specific human movement and action based on images, accelerometer data and inertia measurement unit (IMU) sensors.
Xiang Yang Lim +2 more
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Applied Sciences, 2021 The Massachusetts Eye and Ear Infirmary (MEEI) database is an international-standard training database for voice pathology detection (VPD) systems. However, there is a class-imbalanced distribution in normal and pathological voice samples and different ...
Ziqi Fan +4 more
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Conversion of adverse data corpus to shrewd output using sampling metrics
Visual Computing for Industry, Biomedicine, and Art, 2020 An imbalanced dataset is commonly found in at least one class, which are typically exceeded by the other ones. A machine learning algorithm (classifier) trained with an imbalanced dataset predicts the majority class (frequently occurring) more than the ...
Shahzad Ashraf +4 more
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Active Learning for Imbalanced Datasets
2020 IEEE Winter Conference on Applications of Computer Vision (WACV), 2020 Active learning increases the effectiveness of labeling when only subsets of unlabeled datasets can be processed manually. To our knowledge, existing algorithms are designed under the assumption that datasets are balanced. However, many real-life datasets are actually imbalanced and we propose two adaptations of active learning to tackle imbalance ...
Aggarwal, Umang +2 more
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Distribution-sensitive learning for imbalanced datasets [PDF]
2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG), 2013 Many real-world face and gesture datasets are by nature imbalanced across classes. Conventional statistical learning models (e.g., SVM, HMM, CRY), however, are sensitive to imbalanced datasets. In this paper we show how an imbalanced dataset affects the performance of a standard learning algorithm, and propose a distribution-sensitive prior to deal ...
Song, Yale +2 more
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SSMFN: a fused spatial and sequential deep learning model for methylation site prediction [PDF]
PeerJ Computer Science, 2021 Background Conventional in vivo methods for post-translational modification site prediction such as spectrophotometry, Western blotting, and chromatin immune precipitation can be very expensive and time-consuming.
Favorisen Rosyking Lumbanraja +4 more
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IDPP: Imbalanced Datasets Pipelines in Pyrus
, 2023 We showcase and demonstrate IDPP, a Pyrus-based tool that offers a collection of pipelines for the analysis of imbalanced datasets. Like Pyrus, IDPP is a web-based, low-code/no-code graphical modelling environment for ML and data analytics applications. On a case study from the medical domain, we solve the challenge of re-using AI/ML models that do not
Amandeep Singh, Olga Minguett
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Federated Learning on Clinical Benchmark Data: Performance Assessment
Journal of Medical Internet Research, 2020 BackgroundFederated learning (FL) is a newly proposed machine-learning method that uses a decentralized dataset. Since data transfer is not necessary for the learning process in FL, there is a significant advantage in protecting personal privacy ...
Lee, Geun Hyeong, Shin, Soo-Yong
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Multilayer Feedforward Neural Network for Internet Traffic Classification.
International Journal of Interactive Multimedia and Artificial Intelligence, 2020 Recently, the efficient internet traffic classification has gained attention in order to improve service quality in IP networks. But the problem with the existing solutions is to handle the imbalanced dataset which has high uneven distribution of flows ...
N. Manju, B. S. Harish, N. Nagadarshan
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Offline Reinforcement Learning with Imbalanced Datasets
CoRR, 2023 The prevalent use of benchmarks in current offline reinforcement learning (RL) research has led to a neglect of the imbalance of real-world dataset distributions in the development of models. The real-world offline RL dataset is often imbalanced over the state space due to the challenge of exploration or safety considerations. In this paper, we specify
Li Jiang 0008 +5 more
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