Representation Learning for Motor Imagery Recognition with Deep Neural Network

Learning a Neural-network-based Representation for Open Set Recognition

Open set recognition problems exist in many domains. For example in security, new malware classes emerge regularly; therefore malware classi€cation systems need to identify instances from unknown classes in addition to discriminating between known classes. In this paper we present a neural network based representation for addressing the open set recognition problem. In this representation insta...

Stimulated Deep Neural Network for Speech Recognition

Deep neural networks (DNNs) and deep learning approaches yield state-of-the-art performance in a range of tasks, including speech recognition. However, the parameters of the network are hard to analyze, making network regularization and robust adaptation challenging. Stimulated training has recently been proposed to address this problem by encouraging the node activation outputs in regions of t...

Provide a Deep Convolutional Neural Network Optimized with Morphological Filters to Map Trees in Urban Environments Using Aerial Imagery

Today, we cannot ignore the role of trees in the quality of human life, so that the earth is inconceivable for humans without the presence of trees. In addition to their natural role, urban trees are also very important in terms of visual beauty. Aerial imagery using unmanned platforms with very high spatial resolution is available today. Convolutional neural networks based deep learning method...

Learning classifier systems with neural network representation

Reinforced backpropagation for deep neural network learning

Standard error backpropagation is used in almost all modern deep network training. However, it typically suffers from proliferation of saddle points in high-dimensional parameter space. Therefore, it is highly desirable to design an efficient algorithm to escape from these saddle points and reach a good parameter region of better generalization capabilities, especially based on rough insights a...