Retrieval of images based on low level visual features such as color, texture and shape have proven to have its own set of limitations under different conditions. As the number and size of image databases grows, accurate and efficient content-based image retrieval systems become increasingly important in business and in the everyday lives of people around the world. In this paper we describe a ...

In this paper the RWTH large vocabulary continuous speech recognition (LVCSR) systems developed for the IWSLT2016 evaluation campaign are described. This evaluation campaign focuses on transcribing spontaneous speech from Skype recordings. State-of-the-art bidirectional long shortterm memory (LSTM) and deep, multilingually boosted feed-forward neural network (FFNN) acoustic models are trained a...

Malignant lymphoma is one of the types malignant tumors that can lead to death. The diagnostic method for identifying a histopathological analysis tissue images. Because similar morphological characteristics types, it difficult doctors and specialists manually distinguish lymphomas. Therefore, deep automated learning techniques aim solve this problem help clinicians reconsider their decisions. ...

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

A new hybrid clustering algorithm based on a three-layer feed forward neural network (FFNN), a distribution density function, and a cluster validity index, is presented in this paper. In this algorithm, both feature weighting and sample weighting are considered, and an optimal cluster number is automatically determined by the cluster validity index. Feature weights are learnt via FFNN based on ...

Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...

Utilization of membrane humidifiers is one of the methods commonly used to humidify reactant gases in polymer electrolyte membrane fuel cells (PEMFC). In this study, polymeric porous membranes with different compositions were prepared to be used in a membrane humidifier module and were employed in a humidification test. Three different neural network models were developed to investigate several...

In this study, applicability of Artificial Neural Network (ANN) methods for river flow estimation is investigated. Accurate modeling and forecasting of hydrological processes such as rainfall, rainfall-run off relationship, runoff, is important for management and planning of water resources. To illustrate the capability of ANN for modeling of water resources, Great Menderes River, locate in the...