Zobrazeno 1 - 10
of 52
pro vyhledávání: '"La Grassa, Riccardo"'
Optimization methods (optimizers) get special attention for the efficient training of neural networks in the field of deep learning. In literature there are many papers that compare neural models trained with the use of different optimizers. Each pap
Externí odkaz:
http://arxiv.org/abs/2011.08042
In neural networks, the loss function represents the core of the learning process that leads the optimizer to an approximation of the optimal convergence error. Convolutional neural networks (CNN) use the loss function as a supervisory signal to trai
Externí odkaz:
http://arxiv.org/abs/2009.08796
A large amount of research on Convolutional Neural Networks has focused on flat Classification in the multi-class domain. In the real world, many problems are naturally expressed as problems of hierarchical classification, in which the classes to be
Externí odkaz:
http://arxiv.org/abs/2005.08622
The transfer learning technique is widely used to learning in one context and applying it to another, i.e. the capacity to apply acquired knowledge and skills to new situations. But is it possible to transfer the learning from a deep neural network t
Externí odkaz:
http://arxiv.org/abs/2005.00393
A typical issue in Pattern Recognition is the non-uniformly sampled data, which modifies the general performance and capability of machine learning algorithms to make accurate predictions. Generally, the data is considered non-uniformly sampled when
Externí odkaz:
http://arxiv.org/abs/2004.02273
We present a novel model called One Class Minimum Spanning Tree (OCmst) for novelty detection problem that uses a Convolutional Neural Network (CNN) as deep feature extractor and graph-based model based on Minimum Spanning Tree (MST). In a novelty de
Externí odkaz:
http://arxiv.org/abs/2003.13524
Visualization refers to our ability to create an image in our head based on the text we read or the words we hear. It is one of the many skills that makes reading comprehension possible. Convolutional Neural Networks (CNN) are an excellent tool for r
Externí odkaz:
http://arxiv.org/abs/1909.05663
In this paper, we propose a design methodology for one-class classifiers using an ensemble-of-classifiers approach. The objective is to select the best structures created during the training phase using an ensemble of spanning trees. It takes the bes
Externí odkaz:
http://arxiv.org/abs/1909.04078
One-class classifiers are trained with target class only samples. Intuitively, their conservative modelling of the class description may benefit classical classification tasks where classes are difficult to separate due to overlapping and data imbala
Externí odkaz:
http://arxiv.org/abs/1906.06090
Publikováno v:
In Neurocomputing 22 January 2022 470:217-225
