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標題: Titlebook: Image Understanding using Sparse Representations; Jayaraman J. Tiagarajan,Karthikeyan Natesan Ramamu Book 2014 Springer Nature Switzerland [打印本頁]

作者: fibrous-plaque    時間: 2025-3-21 16:38
書目名稱Image Understanding using Sparse Representations影響因子(影響力)




書目名稱Image Understanding using Sparse Representations影響因子(影響力)學(xué)科排名




書目名稱Image Understanding using Sparse Representations網(wǎng)絡(luò)公開度




書目名稱Image Understanding using Sparse Representations網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Image Understanding using Sparse Representations被引頻次




書目名稱Image Understanding using Sparse Representations被引頻次學(xué)科排名




書目名稱Image Understanding using Sparse Representations年度引用




書目名稱Image Understanding using Sparse Representations年度引用學(xué)科排名




書目名稱Image Understanding using Sparse Representations讀者反饋




書目名稱Image Understanding using Sparse Representations讀者反饋學(xué)科排名





作者: SIT    時間: 2025-3-21 23:12

作者: 迎合    時間: 2025-3-22 01:24
Jayaraman J. Tiagarajan,Karthikeyan Natesan Ramamurthy,Pavan Turaga,Andreas Spanias
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Jayaraman J. Tiagarajan,Karthikeyan Natesan Ramamu
作者: 古代    時間: 2025-3-22 11:59
lobal financial crisis, the government has put forward massive investment stimulus plans and micro-stimulus policies; the authorities should have an in-depth understanding and grasp of the characteristics of China’s economy under the “new normal.” All these together have brought the Chinese economy
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Jayaraman J. Tiagarajan,Karthikeyan Natesan Ramamurthy,Pavan Turaga,Andreas Spanias: to help readers understand China’s economic performance; to forecast the main macroeconomic indicators for the next 8 quarters; and to simulate the effectiveness of macroeconomic policies..978-981-10-9833-8978-981-10-3280-6Series ISSN 2194-7937 Series E-ISSN 2194-7945
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Jayaraman J. Tiagarajan,Karthikeyan Natesan Ramamurthy,Pavan Turaga,Andreas Spanias macroeconomic policies.Includes supplementary material: This book is a quarterly forecast and analysis report on the Chinese economy. It is published twice a year and presents ongoing result from the “China Quarterly Macroeconomic Model (CQMM),” a research project at the Center for Macroeconomic Re
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Jayaraman J. Tiagarajan,Karthikeyan Natesan Ramamurthy,Pavan Turaga,Andreas Spanias macroeconomic policies.Includes supplementary material: This book is a quarterly forecast and analysis report on the Chinese economy. It is published twice a year and presents ongoing results from the “China Quarterly Macroeconomic Model (CQMM),” a research project at the Center for Macroeconomic R
作者: RACE    時間: 2025-3-24 05:06

作者: 儀式    時間: 2025-3-24 06:49
Sparse Representations, that represent the signals sparsely in a transform domain, such as the Fourier [41] or the wavelet domain [42], have been considered. Hence, sparse representation seeks to approximate an input signal by a linear combination of elementary signals. A common metric considered for measuring the sparsit
作者: FELON    時間: 2025-3-24 13:15
Dictionary Learning: Theory and Algorithms,ble to tune the parameters of a pre-defined dictionary, such that the performance over the given set of data is optimized. However, dictionaries that are learned directly from the data result in an improved performance compared to both pre-defined as well as tuned dictionaries. This chapter will foc
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作者: 新奇    時間: 2025-3-24 20:33
Sparse Models in Recognition,ding has been very effective in modeling natural signals, its ability to discriminate different classes of data is not inherent. Since sparse coding algorithms aim to reduce only the reconstruction error, they do not explicitly consider the correlation between the codes, which is crucial for classif
作者: 膠水    時間: 2025-3-25 02:24

作者: 社團    時間: 2025-3-25 06:20
Image Understanding using Sparse Representations978-3-031-02250-0Series ISSN 1559-8136 Series E-ISSN 1559-8144
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作者: 猛然一拉    時間: 2025-3-25 14:25

作者: AGOG    時間: 2025-3-25 19:02
Book 2014ponent in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiting the spa
作者: JOT    時間: 2025-3-25 22:40
Sparse Models in Recognition,nce, adapting this representative model to perform discriminative tasks requires the incorporation of supervisory information into the sparse coding and dictionary learning problems. By introducing the prior knowledge on the sparsity of signals into the traditional machine learning algorithms, novel discriminative frameworks can be developed.
作者: GLUT    時間: 2025-3-26 02:24
Dictionary Learning: Theory and Algorithms,are learned directly from the data result in an improved performance compared to both pre-defined as well as tuned dictionaries. This chapter will focus exclusively on learned dictionaries and their applications in various image processing tasks.
作者: 贊成你    時間: 2025-3-26 06:57

作者: 摻假    時間: 2025-3-26 11:51
1559-8136 ortant component in image understanding, since they emulate the activity of neural receptors in the primary visual cortex of the human brain. Sparse methods have been utilized in several learning problems because of their ability to provide parsimonious, interpretable, and efficient models. Exploiti
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作者: 后來    時間: 2025-3-26 23:36
Was Sie in diesem Buch erwartetobserved during the simulation that the bottoming was observed when the seat travels over the bump. An iterative method is carried out for designing the damper for different weight of operators. A damper is designed for reducing the acceleration and dynamic force of the operator seat.
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Fatimah De’nan,Nor Salwani Hashim,Nor Amirah Yaanicle membrane stress. At the transition point, a strong increase in the orientational order of the red blood cells and a significant decrease of the particle diffusivity are observed. However, the average cell deformation shows no signature of the transition.978-3-8348-2375-5978-3-8348-2376-2
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Bioprocessing and Analytical Development for Virus-Based Therapeutics,ssion of transgenes. Within the scope of this chapter, we provide an overview of important aspects of product and process development and characterization to define critical quality attributes (CQAs) for virus-based ATMPs.
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spective specific substrates produce in every case practically identical unstable electronic systems which include catalytic groups of the active center, a cleaved peptide bond and a water molecule. The idea of a similar mutual orientation of these components in all nonbonded complexes of aspartic p




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