Zobrazeno 1 - 10
of 820
pro vyhledávání: '"Chein‐I Chang"'
Autor:
Yung-Chieh Chang, Chein-I Chang, Yen-Chieh Ouyang, Jyh-Wen Chai, Wen-Hsien Chen, Kuan-Jung Pan, Hsin-Che Wang, Clayton Chi-Chang Chen
Publikováno v:
IEEE Access, Vol 12, Pp 111992-112007 (2024)
White matter hyperintensities (WMHs) are lesion in brain magnetic resonance images generally associated with Alzheimer’s disease (AD) and cognitive decline. Finding WMHs of AD poses a great challenge for diagnosis. This paper interprets a brain MR
Externí odkaz:
https://doaj.org/article/5b5694df8e6043b09dbf2c4d6348f6ab
Publikováno v:
Remote Sensing, Vol 16, Iss 6, p 942 (2024)
Band clustering has been widely used for hyperspectral band selection (BS). However, selecting an appropriate band to represent a band cluster is a key issue. Density peak clustering (DPC) provides an effective means for this purpose, referred to as
Externí odkaz:
https://doaj.org/article/b8d30c7c2155471989d8f987a74b7281
Exploration of Data Scene Characterization and 3D ROC Evaluation for Hyperspectral Anomaly Detection
Publikováno v:
Remote Sensing, Vol 16, Iss 1, p 135 (2023)
Whether or not a hyperspectral anomaly detector is effective is determined by two crucial issues, anomaly detectability and background suppressibility (BS), both of which are very closely related to two factors, the datasets used for a selected hyper
Externí odkaz:
https://doaj.org/article/1e243677f0524b5fbbb059035bb61130
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 4915-4932 (2021)
Orthogonal subspace projection (OSP) is a versatile hyperspectral imaging technique which has shown great potential in dimensionality reduction, target detection, spectral unmixing, etc. However, due to its inherent requirement of prior target knowle
Externí odkaz:
https://doaj.org/article/aeede8949c9148c68e4c23640f20983c
Autor:
C. J. Della Porta, Chein-I Chang
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11775-11788 (2021)
Compressive sensing (CS) has received considerable interest in hyperspectral sensing. Recent articles have also exploited the benefits of CS in hyperspectral image classification (HSIC) in the compressively sensed band domain (CSBD). However, on many
Externí odkaz:
https://doaj.org/article/0300165fe8e54dc8aea522834b537f60
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 12287-12299 (2021)
Enormously hard work of label obtaining leads to the lack of enough annotated samples in the hyperspectral imagery (HSI). The mentioned reality inferred the unsupervised classification performance barely satisfactorily. Unsupervised domain adaptation
Externí odkaz:
https://doaj.org/article/dc035a93d8814a4ebe765cdd4931238a
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 3986-4007 (2020)
Hyperspectral image classification (HSIC) has generated considerable interests over the past years. However, one of challenging issues arising in HSIC is inconsistent classification, which is mainly caused by random training sampling (RTS) of selecti
Externí odkaz:
https://doaj.org/article/d207e658693747a3822fcb5915c71b27
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 2485-2501 (2020)
Convolutional neural networks (CNN) have led to a successful breakthrough for hyperspectral image classification (HSIC). Due to the intrinsic spatial-spectral specificities of a hyperspectral cube, feature extraction with 3-D convolution operation is
Externí odkaz:
https://doaj.org/article/dac13086e68c496b8173e38df0654415
Autor:
Chein-I Chang, Meiping Song, Chunyan Yu, Yulei Wang, Haoyang Yu, Jiaojiao Li, Lin Wang, Hsiao-Chi Li, Xiaorun Li
Publikováno v:
Remote Sensing, Vol 14, Iss 20, p 5111 (2022)
Hyperspectral imaging (HSI) has emerged as a promising, advanced technology in remote sensing and has demonstrated great potential in the exploitation of a wide variety of data. In particular, its capability has expanded from unmixing data samples an
Externí odkaz:
https://doaj.org/article/861a1c8ee01f4fd48dde5669045da252
Autor:
Chi-Chang Clayton Chen, Jyh-Wen Chai, Hung-Chieh Chen, Hsin Che Wang, Yung-Chieh Chang, Yi-Ying Wu, Wen-Hsien Chen, Hsian-Min Chen, San-Kan Lee, Chein-I Chang
Publikováno v:
IEEE Access, Vol 7, Pp 124674-124687 (2019)
White matter hyperintensities (WMH) generally can be detected and diagnosed by magnetic resonance imaging (MRI). It has been pointed out that WMH is closely associated with stroke, cognitive impairment, dementia, and even is very relevant to the incr
Externí odkaz:
https://doaj.org/article/ce9a14b0eecd4f22b356b95f35038d7b