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	Efficient Brain Decoding Based on Adaptive EEG Channel Selection and Transformation 期刊论文 OAI收割 IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2022, 页码: 10 作者: Wang, Jiaxing; Shi, Lei; Wang, Weiqun \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2022/06/06 Electroencephalography Decoding Brain modeling Computational modeling Optimized production technology Feature extraction Data models Channel selection channel transformation brain decoding computational cost classification accuracy
	Prediction of Potentially Suitable Distributions of Codonopsis pilosula in China Based on an Optimized MaxEnt Model 期刊论文 OAI收割 FRONTIERS IN ECOLOGY AND EVOLUTION, 2021, 卷号: 9, 页码: 17 作者: Yan, Huyong; He, Jiao; Xu, Xiaochuan; Yao, Xinyu; Wang, Guoyin \| 收藏 \| 浏览/下载：39/0 \| 提交时间：2022/08/22 optimized MaxEnt Codonopsis pilosula regularization multiplier feature combination potential distribution multivariate environmental similarity surface analysis
	Object-oriented Multi-feature Fusion Change Detection Method for High Resolution Remote Sensing Image 会议论文 OAI收割 2009 17th International Conference on Geoinformatics, Vols 1 and 2, New York Wang, Wen-jie; Zhao, Zhong-ming; Zhu, Hai-qing 收藏 \| 浏览/下载：15/0 \| 提交时间：2014/12/07 object-oriented segment optimized feature spectral feature texture feature shape feature fusion CHANGE-VECTOR ANALYSIS LAND-COVER CLASSIFICATION
	Optical system design with high resolution and large field of view for the remote sensor (EI CONFERENCE) 会议论文 OAI收割 Chang J.; Weng Z.-C.; Wang Y.-T.; Cheng D.-W.; Jiang H.-L. 收藏 \| 浏览/下载：29/0 \| 提交时间：2013/03/25 In this paper we are presenting a design method and its results for a space optical system with high resolution and wide field of view. This optical system can be used both in infrared and visible configurations. The designing of this system is based on an on-axis three-mirror anastigmatic (TMA) system. Here the on-axis concept allows wide field of view (FOV) enabling a diversity of designs available for the Multi-Object Spectrometer instruments optimized for low scattered and low emissive light. The available FOVs are upto 1 in both spectrum ranges whereas the available aperture range is F/15 - F/10. The final optical system is a three-mirror telescope with two on-axis and one off-axis segment and its resolution is 0.3m or even lower. The distinguished feature of this design is that it maintains diffraction-limited image at wide wavelengths. The technological developments in the field of computer generated shaping of large-sized optical surface details with diffraction-limited imagery have opened new avenues towards the designing techniques. Such techniques permit us to expand these technological opportunities to fabricate the aspherical off-axis mirrors for a complex configuration.
	Multiwavelet based multispectral image fusion for corona detection (EI CONFERENCE) 会议论文 OAI收割 ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China 作者: Wang X.; Yang H.-J.; Sui Y.-X.; Yan F.; Yan F. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 Image fusion refers to the integration of complementary information provided by various sensors such that the new images are more useful for human or machine perception. Multiwavelet transform has simultaneous orthogonality symmetry compact support and vanishing moment which are not possible with scalar wavelet transform. Multiwavelet analysis can offer more precise image analysis than wavelet multiresolution analysis. In this paper a new image fusion algorithm based on discrete multiwavelet transform (DMWT) to fuse the dual-spectral images generated from the corona detection system is presented. The dual-spectrum detection system is used to detect the corona and indicate its exact location. The system combines a solar-blind UV ICCD with a visible camera where the UV image is useful for detecting UV emission from corona and the visible image shows the position of the corona. The developed fusion algorithm is proposed considering the feature of the UV and visible images adequately. The source images are performed at the pixel level. First a decomposition step is taken with the DMWT. After the decomposition step a pyramid for each source image in each level can be obtained. Then an optimized coefficient fusion rule consisting of activity level measurement coefficient combining and consistency verification is used to acquire the fused coefficients. This process reduces the impulse noise of UV image. Finally a new fused image is obtained by reconstructing the fused coefficients using inverse DMWT. This image fusion algorithm has been applied to process the multispectral UV/visible images. Experimental results show that the proposed method outperforms the discrete wavelet transform based approach.