The ability of a computer system to be able understand surroundings and elements think like human being process the information has always been major point focus in field Computer Science. One ways achieve this artificial intelligence is Visual Question Answering. Answering (VQA) trained which can answer questions associated given image Natural Language. VQA generalized used any image-based sce...

This paper presents a novel method for processing automatic speech recognition (ASR) lattices (and generally weighted finite state acceptors) in feed-forward artificial neural networks. It is based on the existing work focused on the text classification using convolutional neural networks (CNNs). The presented method generalizes the convolutional layer of the neural network so that it is able t...

Very deep convolutional neural networks (CNNs) yield state of the art results on a wide variety of visual recognition problems. A number of state of the the art methods for image recognition are based on networks with well over 100 layers and the performance vs. depth trend is moving towards networks in excess of 1000 layers. In such extremely deep architectures the vanishing or exploding gradi...

Brain tumor segmentation in magnetic resonance imaging (MRI) is helpful for diagnostics, growth rate prediction, tumor volume measurements and treatment planning of brain tumor. The difficulties for brain tumor segmentation are mainly due to high variation of brain tumors in size, shape, regularity, location, and their heterogeneous appearance (e.g., contrast, intensity and texture variation fo...