Titlebook: Image Analysis and Recognition; 17th International C Aurélio Campilho,Fakhri Karray,Zhou Wang Conference proceedings 2020 Springer Nature S

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Jo?o F. Teixeira,António M. Carreiro,Rute M. Santos,Hélder P. Oliveiran of organs and tissues and the production of energy.’ Malnutrition results when this process goes wrong, whether because of problems on the intake side or because of problems in processing the intake. There are various types of malnutrition including protein-energy malnutrition and specific micro-n

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0302-9743 thalmic diseases; and grand challenge on automatic lung cancer patient management..Due to the corona pandemic, ICIAR 2020 was held virtually only..978-3-030-50515-8978-3-030-50516-5Series ISSN 0302-9743 Series E-ISSN 1611-3349

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A Multiscale Energy-Based Time-Domain Approach for Interference Detection in Non-stationary Signals-frequency representations or imaging methods. The performance of the proposed method is evaluated through several numerical simulations and comparative studies with the state of the art Rényi entropy based method. Finally, an example concerning a potential application to simulated micro-doppler human gait data is provided.

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Anomaly Detection for Images Using Auto-encoder Based Sparse Representation proposed model over other variants of auto-encoder based anomaly detection models in terms of AUC. In addition, the results show that the sparse representation based anomaly detection method could apply to different scenarios.

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0302-9743 nd Recognition, ICIAR 2020, held in Póvoa de Varzim, Portugal, in June 2020..The 54 full papers presented together with 15 short papers were carefully reviewed and selected from 123 submissions. The papers are organized in the following topical sections: image processing and analysis; video analysis

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Combining Mixture Models and Spectral Clustering for Data Partitioningthat clusters of any shape are automatically discovered. The proposed method shows a significant improvement compared to the classical Gaussian Mixture clustering approach and promising results against well-known partitioning algorithms with respect to the number of parameters.

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Theoretical Insights into the Use of Structural Similarity Index in Generative Models and Inferentiaonditional generated moment matching networks. Then, we explain how to use SSIM distance in variational and adversarial autoencoders and unconditional and conditional Generative Adversarial Networks (GANs). Finally, we propose to use SSIM distance rather than . norm in least squares GAN.

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