Machine learning has been expansively examined with data classification as the most popularly researched subject. The accurateness of prediction is impacted by provided to algorithm. Meanwhile, utilizing a large amount may incur costs especially in collection and preprocessing. Studies on feature selection were mainly establish techniques that can decrease number utilized features (attributes) ...

The segmentation of ground-based cloud images is the basis for obtaining numerous parameters. To achieve high-precision adaptive image requirements, this study designs a lightweight method named CloudDeepLabV3+ that integrates multi-scale features aggregation and multi-level attention feature enhancement. Firstly, novel EfficientNetV2-S designed as extraction backbone to reduce network Secondly...

Introduction: Mental arithmetic analysis based on Electroencephalogram (EEG) signal for monitoring the state of the user’s brain functioning can be helpful for understanding some psychological disorders such as attention deficit hyperactivity disorder, autism spectrum disorder, or dyscalculia where the difficulty in learning or understanding the arithmetic exists. Most mental arithmetic recogni...

Hyperspectral sensors provide a large number of spectral bands. This massive and complex data structure of hyperspectral images presents a challenge to traditional data processing techniques. Therefore, reducing the dimensionality of hyperspectral images without losing important information is a very important issue for the remote sensing community. We propose to use overlap-based feature weigh...