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

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Weighted Fisher Discriminant Analysis in the Input and Feature Spacesly. Although, in FDA, all the pairs of classes are treated the same way, some classes are closer than the others. Weighted FDA assigns weights to the pairs of classes to address this shortcoming of FDA. In this paper, we propose a cosine-weighted FDA as well as an automatically weighted FDA in which
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Backprojection for Training Feedforward Neural Networks in the Input and Feature Spacesorks to gain more insights into networks. In this paper, we propose a new algorithm for training feedforward neural networks which is fairly faster than backpropagation. This method is based on projection and reconstruction where, at every layer, the projected data and reconstructed labels are force
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A Multiscale Energy-Based Time-Domain Approach for Interference Detection in Non-stationary Signalsns, like micro-doppler human gait analysis, surveillance or medical data analysis. State-of-the-art methods are not capable yet to correctly estimate individual modes if their instantaneous frequencies laws are not separable. The knowledge of time instants where modes interference occurs could repre
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MSPNet: Multi-level Semantic Pyramid Network for Real-Time Object Detection years. However, modern approaches usually compromise detection accuracy to achieve real-time inference speed. Some light weight top-down CNN detectors suffer from problems of spatial information loss and lack of multi-level semantic information. In this paper, we introduce an efficient CNN architec
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