Clustering Analysis for Classifying Student Academic Performance in Higher Education
Applied Sciences, 2022 There are three income categories for Malaysians: the top 20% (T20), the middle 40% (M40), and the bottom 40% (B40). The government has extended B40′s access to higher education to eliminate socioeconomic disparities and improve their lives.
Ahmad Fikri Mohamed Nafuri +4 more
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Dimensionality Reduction by Similarity Distance-Based Hypergraph Embedding
Atmosphere, 2022 Dimensionality reduction (DR) is an essential pre-processing step for hyperspectral image processing and analysis. However, the complex relationship among several sample clusters, which reveals more intrinsic information about samples but cannot be ...
Xingchen Shen, Shixu Fang, Wenwen Qiang
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ENTROPY BASED GREEDY UNSUPERVISED FEATURE SELECTION METHOD USING ROUGH SET THEORY FOR CLASSIFICATION
ICTACT Journal on Soft Computing, 2022 Feature selection technique attempts to select and remove irrelevant features while ensuring that an informative subset of features remains in the dataset.
Rubul Kumar Bania, Satyajit Sarmah
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Change Alignment-Based Image Transformation for Unsupervised Heterogeneous Change Detection
Remote Sensing, 2022 Change detection (CD) with heterogeneous images is currently attracting extensive attention in remote sensing. In order to make heterogeneous images comparable, the image transformation methods transform one image into the domain of another image, which ...
Kuowei Xiao, Yuli Sun, Lin Lei
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Self-Collaborative Unsupervised Hashing for Large-Scale Image Retrieval
IEEE Access, 2022 Learning based hashing approaches have achieved considerable success in large-scale image retrieval due to the query effectiveness and efficiency. However, most studies highly rely on supervised knowledge like data labels, thus might fail in unsupervised
Hongmin Zhao, Zhigang Luo
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A Survey on Semi-, Self- and Unsupervised Learning for Image Classification
IEEE Access, 2021 While deep learning strategies achieve outstanding results in computer vision tasks, one issue remains: The current strategies rely heavily on a huge amount of labeled data.
Lars Schmarje +3 more
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Unsupervised Few-Shot Feature Learning via Self-Supervised Training
Frontiers in Computational Neuroscience, 2020 Learning from limited exemplars (few-shot learning) is a fundamental, unsolved problem that has been laboriously explored in the machine learning community.
Zilong Ji +4 more
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A Visualization Framework for Unsupervised Analysis of Latent Structures in SAR Image Time Series
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 Openly available satellite image time series (SITS) are considered an important resource for spatiotemporal change monitoring. However, obtaining semantically annotated datasets for such tasks is an expensive affair.
Chandrabali Karmakar +3 more
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IEEE Access, 2020 Unsupervised anomaly detection for spatio-temporal data has extensive use in a wide variety of applications such as earth science, traffic monitoring, fraud and disease outbreak detection.
Yildiz Karadayi +2 more
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Over-the-Counter Use of Medical Abortion Pills: A Prospective Cohort Study [PDF]
Journal of Clinical and Diagnostic Research, 2023 Introduction: Medical abortion is a safe intervention in the first trimester that requires access to accurate information and the support of a trained healthcare provider.
Reema Kumari +2 more
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