Academic literature on the topic 'Urban hydiene'

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Journal articles on the topic "Urban hydiene"

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Qi, Huiqing, Shengli Tan, and Zhichao Li. "Anisotropic Weighted Total Variation Feature Fusion Network for Remote Sensing Image Denoising." Remote Sensing 14, no. 24 (2022): 6300. http://dx.doi.org/10.3390/rs14246300.

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Remote sensing images are widely applied in instance segmentation and objetive recognition; however, they often suffer from noise, influencing the performance of subsequent applications. Previous image denoising works have only obtained restored images without preserving detailed texture. To address this issue, we proposed a novel model for remote sensing image denoising, called the anisotropic weighted total variation feature fusion network (AWTVF2Net), consisting of four novel modules (WTV-Net, SOSB, AuEncoder, and FB). AWTVF2Net combines traditional total variation with a deep neural networ
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Hossain, Mazharul, Mohammed Younis, Aaron Robinson, Lan Wang, and Chrysanthe Preza. "Greedy Ensemble Hyperspectral Anomaly Detection." Journal of Imaging 10, no. 6 (2024): 131. http://dx.doi.org/10.3390/jimaging10060131.

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Hyperspectral images include information from a wide range of spectral bands deemed valuable for computer vision applications in various domains such as agriculture, surveillance, and reconnaissance. Anomaly detection in hyperspectral images has proven to be a crucial component of change and abnormality identification, enabling improved decision-making across various applications. These abnormalities/anomalies can be detected using background estimation techniques that do not require the prior knowledge of outliers. However, each hyperspectral anomaly detection (HS-AD) algorithm models the bac
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Alkhatib, Mohammed Q., and Miguel Velez-Reyes. "Improved Spatial-Spectral Superpixel Hyperspectral Unmixing." Remote Sensing 11, no. 20 (2019): 2374. http://dx.doi.org/10.3390/rs11202374.

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In this paper, an unsupervised unmixing approach based on superpixel representation combined with regional partitioning is presented. A reduced-size image representation is obtained using superpixel segmentation where each superpixel is represented by its mean spectra. The superpixel image representation is then partitioned into regions using quadtree segmentation based on the Shannon entropy. Spectral endmembers are extracted from each region that corresponds to a leaf of the quadtree and combined using clustering into endmember classes. The proposed approach is tested and validated using the
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Guo, Huinan, Hua Wang, Xiaodong Song, and Zhongling Ruan. "Anomaly Detection of Remote Sensing Images Based on the Channel Attention Mechanism and LRX." Applied Sciences 13, no. 12 (2023): 6988. http://dx.doi.org/10.3390/app13126988.

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Anomaly detection of remote sensing images has gained significant attention in remote sensing image processing due to their rich spectral information. The Local RX (LRX) algorithm, derived from the Reed–Xiaoli (RX) algorithm, is a hyperspectral anomaly detection method that focuses on identifying anomalous pixels in hyperspectral images by exploiting local statistics and background modeling. However, it is still susceptible to the noises in the Hyperspectral Images (HSIs), which limits its detection performance. To address this problem, a hyperspectral anomaly detection algorithm based on chan
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Dissertations / Theses on the topic "Urban hydiene"

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Kumar, Amit. "Hazard rating of municipal solid waste (MSW) dumps considering potential for contamination of air, surface water and groundwater." Thesis, IIT Delhi, 2016. http://localhost:8080/iit/handle/2074/7087.

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Conference papers on the topic "Urban hydiene"

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Kalman, Linda S., and Edward M. Bassett III. "Classification and material identification in an urban environment using HYDICE hyperspectral data." In Optical Science, Engineering and Instrumentation '97, edited by Michael R. Descour and Sylvia S. Shen. SPIE, 1997. http://dx.doi.org/10.1117/12.283843.

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