In scene parsing, the wide-range contextual information is not effectively encoded. Scene parsing provides segmentation and determines an scene into different regions associated with semantic categories. The main objective of scene parsing is to reduce semantic gap between humans and computer machines on scene understanding. The scenes parsing applications are object detection, text detection o...

Maintaining environmental stability in a dynamic system is a difficult challenge. In your living room, when you set your thermostat to 68 degrees the actual temperature cycles above and below 68 degrees. We attempt to use a Recurrent Neural Network (RNN) in an Aquarium Control System that reduces such environmental swings (see Figure 1).

We address fine-grained entity classification and propose a novel attention-based recurrent neural network (RNN) encoderdecoder that generates paths in the type hierarchy and can be trained end-to-end. We show that our model performs better on fine-grained entity classification than prior work that relies on flat or local classifiers that do not directly model hierarchical structure.

We introduce an exceptionally simple gated recurrent neural network (RNN) that achieves performance comparable to well-known gated architectures, such as LSTMs and GRUs, on the word-level language modeling task. We prove that our model has simple, predicable and non-chaotic dynamics. This stands in stark contrast to more standard gated architectures, whose underlying dynamical systems exhibit c...

Recently, neural-network-based adaptive control technique has attracted increasing attentions, because it has provided an efficient and effective way in the control of complex nonlinear or ill-defined systems (Duarte-Mermoud et al., 2005; Hsu et al., 2006; Lin and Hsu, 2003; Lin et al., 1999; Peng et al. 2004). The key elements of this success are the approximation capabilities of the neural ne...

Recurrent Neural Networks (RNNs) have obtained excellent result in many natural language processing (NLP) tasks. However, understanding and interpreting the source of this success remains a challenge. In this paper, we propose Recurrent Memory Network (RMN), a novel RNN architecture, that not only amplifies the power of RNN but also facilitates our understanding of its internal functioning and ...

Integration of Global Positioning System (GPS) and Inertial Navigation System (INS) has been extensively used in aircraft applications like autopilot, to provide better navigation, even in the absence of GPS. Even though Kalman Filter (KF) based GPS/INS integration provides a robust solution to navigation, it requires prior knowledge of the error model of INS, which increases the complexity of ...

Recurrent neural networks (RNN) have traditionally been of great interest for their capacity to store memories. In past years, several works have been devoted to determine the maximum storage capacity of RNN, especially for the case of the Hopfield network, the most popular kind of RNN. Analyzing the thermodynamic limit of the statistical properties of the Hamiltonian corresponding to the Hopfi...