標(biāo)題: Titlebook: Computational Intelligence for Remote Sensing; Manuel Gra?a,Richard J. Duro Book 2008 Springer-Verlag Berlin Heidelberg 2008 Markov.Markov [打印本頁] 作者: 短暫 時間: 2025-3-21 18:36
書目名稱Computational Intelligence for Remote Sensing影響因子(影響力)
書目名稱Computational Intelligence for Remote Sensing影響因子(影響力)學(xué)科排名
書目名稱Computational Intelligence for Remote Sensing網(wǎng)絡(luò)公開度
書目名稱Computational Intelligence for Remote Sensing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Computational Intelligence for Remote Sensing被引頻次
書目名稱Computational Intelligence for Remote Sensing被引頻次學(xué)科排名
書目名稱Computational Intelligence for Remote Sensing年度引用
書目名稱Computational Intelligence for Remote Sensing年度引用學(xué)科排名
書目名稱Computational Intelligence for Remote Sensing讀者反饋
書目名稱Computational Intelligence for Remote Sensing讀者反饋學(xué)科排名
作者: 戰(zhàn)勝 時間: 2025-3-21 23:31
Remote Sensing Data Compression,e a special challenge, and multiple efficient image compression systems have appeared. This chapter contributes an overview of several techniques for image coding systems, focusing on lossy approaches.作者: Antigen 時間: 2025-3-22 01:25 作者: GREG 時間: 2025-3-22 07:33 作者: Lucubrate 時間: 2025-3-22 09:11
On Content-Based Image Retrieval Systems for Hyperspectral Remote Sensing Images, the literature regarding remote sensing images. Our own focus is on hyperspectral images. The approach we are pursuing is that of characterizing the spectral content of the image through the set of endmembers induced from it. We describe some ideas and numerical experiments for a system that would 作者: savage 時間: 2025-3-22 16:46 作者: savage 時間: 2025-3-22 17:16 作者: 連鎖 時間: 2025-3-22 21:52
Parallel Classification of Hyperspectral Images Using Neural Networks,est-generation Earth observation instruments is expected to introduce extremely high computational requirements in neural network-based algorithms for classification of high-dimensional data sets such as hyperspectral images, with hundreds of spectral channels and very fine spatial resolution. A sig作者: concentrate 時間: 2025-3-23 05:02 作者: Medicare 時間: 2025-3-23 06:53 作者: 支架 時間: 2025-3-23 10:10 作者: FEAT 時間: 2025-3-23 16:04 作者: 果仁 時間: 2025-3-23 18:55 作者: 剝皮 時間: 2025-3-24 00:07 作者: Mitigate 時間: 2025-3-24 06:10 作者: 埋伏 時間: 2025-3-24 07:39
1860-949X sses of images dealt with throughout the book are mostly multispectral-hyperspectral images, though there are some instances of processing Synthetic Aperture Radar images..978-3-642-09823-9978-3-540-79353-3Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: 發(fā)誓放棄 時間: 2025-3-24 13:07 作者: Homocystinuria 時間: 2025-3-24 18:38
A Multiobjective Evolutionary Algorithm for Hyperspectral Image Watermarking,ent these conflicting criteria, and that can be efficiently evaluated. The application of an evolutionary algorithm (MOGA) to the optimal watermarking hyperspectral images is presented. Given an appropriate initialization, the algorithm can perform the search for the optimal mark placement in the or作者: molest 時間: 2025-3-24 19:04 作者: cluster 時間: 2025-3-25 00:12
Parallel Spatial-Spectral Processing of Hyperspectral Images, of some of the proposed techniques are also developed to satisfy time-critical constraints in remote sensing applications, using NASA’s Thunderhead Beowulf cluster for demonstration purposes throughout the chapter. Combined, the different topics covered by this chapter offer a thoughtful perspectiv作者: FICE 時間: 2025-3-25 04:44 作者: 全能 時間: 2025-3-25 07:46
A Computation Reduced Technique to Primitive Feature Extraction for Image Information Mining Via thhives then in multimedia image archives. Hence, the adoption of new technologies that allow the accessibility of remote sensing data based on content and semantics is required to overcome this challenge and increase useful exploitation of the data [1, 2, 3].作者: 展覽 時間: 2025-3-25 12:45 作者: conference 時間: 2025-3-25 18:42
Automatic Preprocessing and Classification System for High Resolution Ultra and Hyperspectral Image spectral dimension. Regardless of the application of the images, the analysis methods employed must deal with large quantities of data efficiently [1]. Originally, imaging spectroradiometers were used as airborne or spaceborne remote sensing instruments. During the last decade, spectral imaging has作者: FLING 時間: 2025-3-25 21:42
Unsupervised Change Detection from Multichannel SAR Data by Markov Random Fields,y) SAR represents an option with improved potential: as compared with single-channel SAR, it is expected to provide an increased discrimination capability, while maintaining its insensitivity to atmospheric and illumination issues. This potential is also reinforced by the availability of multichanne作者: Oafishness 時間: 2025-3-26 00:45
Public Health Communication and Growthperposition of the radiation reflected in three broad band of the spectrum, typically blue, green and red bands. Much more information can be obtained if the photographs are taken in tens or hundreds of different spectral bands. Imaging spectrometers do this work. They take separated images at narro作者: palliative-care 時間: 2025-3-26 07:59
Albert Anani-Bossman,Isaac Abeku Blanksonent these conflicting criteria, and that can be efficiently evaluated. The application of an evolutionary algorithm (MOGA) to the optimal watermarking hyperspectral images is presented. Given an appropriate initialization, the algorithm can perform the search for the optimal mark placement in the or作者: 雪上輕舟飛過 時間: 2025-3-26 08:57 作者: orthodox 時間: 2025-3-26 14:02
Sustainability and Communication, of some of the proposed techniques are also developed to satisfy time-critical constraints in remote sensing applications, using NASA’s Thunderhead Beowulf cluster for demonstration purposes throughout the chapter. Combined, the different topics covered by this chapter offer a thoughtful perspectiv作者: FLUSH 時間: 2025-3-26 19:20
Sergei A. Samoilenko,Marlene Laruelleor classification of hyperspectral imagery using neural networks are presented and discussed. Experimental results are provided from the viewpoint of both classification accuracy and parallel performance on a variety of parallel computing platforms, including two networks of workstations at Universi作者: 起皺紋 時間: 2025-3-26 23:13
https://doi.org/10.1007/978-3-030-27253-1hives then in multimedia image archives. Hence, the adoption of new technologies that allow the accessibility of remote sensing data based on content and semantics is required to overcome this challenge and increase useful exploitation of the data [1, 2, 3].作者: fringe 時間: 2025-3-27 03:34 作者: 制定 時間: 2025-3-27 08:10 作者: 小畫像 時間: 2025-3-27 09:28 作者: creditor 時間: 2025-3-27 16:52
Computational Intelligence for Remote Sensing978-3-540-79353-3Series ISSN 1860-949X Series E-ISSN 1860-9503 作者: municipality 時間: 2025-3-27 21:31 作者: 創(chuàng)作 時間: 2025-3-27 22:43
Remote Sensing Data Compression,e a special challenge, and multiple efficient image compression systems have appeared. This chapter contributes an overview of several techniques for image coding systems, focusing on lossy approaches.作者: 虛弱 時間: 2025-3-28 04:45
Public Health Communication and Growth, allowing to obtain a spectral signature of each point in the scene. They are applied to perform many different tasks such as accurate mapping of wide areas, object identification and recognition, target detection, process monitoring and control, clinical diagnosis imaging and environment assessmen作者: 等待 時間: 2025-3-28 09:13 作者: separate 時間: 2025-3-28 13:03
Albert Anani-Bossman,Isaac Abeku Blanksonn the remote sensing community. Watermarking techniques help to solve the problems raised by this issue. In this paper we elaborate on the proposition of an optimal placement of the watermark image in a hyperspectral image. We propose an evolutionary algorithm for the digital semi-fragile watermakin作者: corn732 時間: 2025-3-28 17:32 作者: 厭倦嗎你 時間: 2025-3-28 22:00
https://doi.org/10.1007/978-3-658-29122-8 the literature regarding remote sensing images. Our own focus is on hyperspectral images. The approach we are pursuing is that of characterizing the spectral content of the image through the set of endmembers induced from it. We describe some ideas and numerical experiments for a system that would 作者: 過渡時期 時間: 2025-3-29 01:25
https://doi.org/10.1007/978-3-319-18005-2 of the gathered information. The target areas are characterized by zones with different interest levels. We model the interest variable as an “importance function” that assigns a quantitative reference to each point. Due to the nature of WSNs, the sensor deployment must guarantee that the informati作者: Generator 時間: 2025-3-29 04:18 作者: 沖突 時間: 2025-3-29 10:10
Sergei A. Samoilenko,Marlene Laruelleest-generation Earth observation instruments is expected to introduce extremely high computational requirements in neural network-based algorithms for classification of high-dimensional data sets such as hyperspectral images, with hundreds of spectral channels and very fine spatial resolution. A sig作者: floodgate 時間: 2025-3-29 13:55 作者: 原諒 時間: 2025-3-29 17:34
https://doi.org/10.1007/978-3-030-27253-1fferent domains because data accessibility is limited to queries based on geographical coordinates, time of acquisitions, sensor types, and acquisition mode. Research in knowledge discovery from remote sensing archives has been propelled in the last few years by the adoption of newer technologies. H作者: Pepsin 時間: 2025-3-29 22:26 作者: 憂傷 時間: 2025-3-30 03:21
https://doi.org/10.1007/978-3-030-27253-1 a total burnt area of 740,000 hectares [22]. Even if in some countries according to the national burnt area statistics the problem seems to be under control and of steady or decreasing magnitude, in regions like the western Iberian Peninsula or large parts of North America the trend is worryingly o作者: 口味 時間: 2025-3-30 05:08 作者: FRAUD 時間: 2025-3-30 09:27
Competition with Fluctuating Demand, data processing..In the near future the international proliferation of remote sensing devices will require an ever increasing number of high–resolution systems with lightweight instruments for application in small satellites and light planes, as well as a reduction of costs. One important tool used作者: 蟄伏 時間: 2025-3-30 15:27 作者: 門窗的側(cè)柱 時間: 2025-3-30 18:34 作者: 憤慨點吧 時間: 2025-3-30 21:36 作者: 大包裹 時間: 2025-3-31 02:12 作者: alabaster 時間: 2025-3-31 08:48 作者: Adrenal-Glands 時間: 2025-3-31 12:34 作者: 逃避系列單詞 時間: 2025-3-31 16:51
Competition with Fluctuating Demand, in remote sensing is imaging spectroscopy, also known as multi, hyper or ultraspectral remote sensing. It consists in the acquisition of images where for each spatial resolution element a part of the electromagnetic spectrum sampled at different rates is measured [1,2].
