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<italic>Unsupervised feature selection (UFS)</italic> is an important technology for dimensionality reduction and has gained great interest in a wide range of fields. Recently, most popular methods are spectral-based which frequently use adaptive graph ...

Graph-based multi-view clustering methods have demonstrated impressive outcomes in capturing the underlying manifold structure of data, leading to improved clustering performance. However, conventional graph-based methods overlook the significance of ...

Unsupervised feature selection has attracted increasing attention for its promising performance on high dimensional data with higher dimensionality and more expensive labeling costs. Existing unsupervised feature selection methods mostly assume ...

Apple leaf diseases have significant impacts on apple quality and productivity. So, the implementation of accurate disease detection in the early stages is a powerful guarantee for the rapid and high-quality development of the apple industry. However, ...

• This paper proposes a method to replace the linear mapping-based spectral analysis with neural networks, which is more appropriate to learn the nonlinear ...

Unsupervised feature selection (UFS), which selects the most important feature subset and eliminates the unnecessary information for the upcoming data analysis, is a significant problem in machine learning and has been explored for ...

Apple leaf diseases seriously affect the quality of apples and may lead to yield losses, detecting apple leaf diseases accurately can prevent diseases from spreading and promote the healthy growth of the industry. However, recent studies cannot achieve ...

Unsupervised feature selection (UFS) plays a critical role in the maintenance of representative feature subset from high dimensional data. Both the spectral analysis model and the self-expression model are effective in selecting important ...

Aphids, brown spots, mosaics, rusts, powdery mildew and Alternaria blotches are common types of early apple leaf pests and diseases that severely affect the yield and quality of apples. Recently, deep learning has been regarded as the best classification ...

Feature selection usually takes unsupervised way to preprocess the data before clustering. In the unsupervised feature selection, the embedding based method can capture more discriminative information contained in data compared to the other ...

Using a natural language sentence to describe the content of an image is a challenging but very important task. It is challenging because a description must not only capture objects contained in the image and the relationships among them, but also be ...