Results 41 to 50 of about 314,709 (295)
Mixed-Noise Band Selection for Hyperspectral Images
IEEE Access, 2020 Hyperspectral images (HSIs) with abundant spectral information are generally susceptible to various types of noise, such as Gaussian noise and stripe noise.
Zhen Li, Chenwei Deng, Yun Huang
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Problem-based band selection for hyperspectral images [PDF]
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017 This paper addresses the band selection of a hyperspectral image. Considering a binary classification, we devise a method to choose the more discriminating bands for the separation of the two classes involved, by using a simple algorithm: single-layer neural network. After that, the most discriminative bands are selected, and the resulting reduced data
Habermann, Mateus +2 more
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Adaptive Distance-Based Band Hierarchy (ADBH) for Effective Hyperspectral Band Selection [PDF]
IEEE Transactions on Cybernetics, 2022 Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) processing. Although many unsupervised band selection (UBS) approaches have been developed in the last decades, a flexible and robust method is still lacking.
He Sun 0009 +6 more
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Remote Sensing, 2023 This article provides insights into the optical signatures of plastic litter based on a published laboratory-scale reflectance data set (350–2500 nm) of dry and wet plastic debris under clear and turbid waters using different band selection techniques ...
Mohammadali Olyaei, Ardeshir Ebtehaj
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A Split-and-Merge Approach for Hyperspectral Band Selection [PDF]
IEEE Geoscience and Remote Sensing Letters, 2017 The problem of band selection (BS) is of great importance to handle the curse of dimensionality for hyperspectral image (HSI) applications (e.g., classification). This letter proposes an unsupervised BS approach based on a split-and-merge concept. This new approach provides relevant spectral sub-bands by splitting the adjacent bands without violating ...
Shaheera Rashwan, Nicolas Dobigeon
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Gait feature subset selection by mutual information [PDF]
, 2007 Feature selection is an important pre-processing step for pattern recognition. It can discard irrelevant and redundant information that may not only affect a classifier’s performance, but also tell against system’s efficiency.
Mark S. Nixon +5 more
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A multi-band high selectivity frequency selective surface for ka-band applications
2017 10th Global Symposium on Millimeter-Waves, 2017 This paper proposes a new method to implement Frequency Selective Surfaces (FSSs) with sharp band edge transitions suitable for millimetres wave applications. A bandpass FSS can be realized by combining two bandstop FSS structures on the same plane.
Hussein, Muaad +3 more
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Attention Networks for Band Weighting and Selection in Hyperspectral Remote Sensing Image Classification [PDF]
, 2019 Hyperspectral imaging is widely used in remote sensing because of its capability to capture the detailed spectral reflection of the ground object. The acquired rich band information brings significant benefits to better discriminate the target pixels ...
Wang, J, Huang, W, Zhou, J, Chen, JF
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Underwater Hyperspectral Target Detection with Band Selection [PDF]
, 2020 Compared to multi-spectral imagery, hyperspectral imagery has very high spectral resolution with abundant spectral information. In underwater target detection, hyperspectral technology can be advantageous in the sense of a poor underwater imaging ...
Xudong Sun +5 more
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Alpha-band rhythms in visual task performance: phase-locking by rhythmic sensory stimulation [PDF]
, 2012 Oscillations are an important aspect of neuronal activity. Interestingly, oscillatory patterns are also observed in behaviour, such as in visual performance measures after the presentation of a brief sensory event in the visual or another modality. These
Gregor Thut +26 more
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