This paper describes a novel design environment for cognitive systems tailored to the needs of flexibility, speed and transparence demanded in numerous application domains as e.g., automated visual inspection for quality control, mechatronics, medical applications, and other cognitive tasks. Our QuickCog design environment combines methods from statistical pattern recognition, neural networks, ...

Face recognition is an active research area in various streams such as pattern recognition, image processing. The Strong need of Face Recognition is personal identification and recognition without the cooperation of the participants. This paper presents face recognition using wavelet transform. A face recognition system follow these steps image decomposition, detection, feature extraction, and ...

Visual question answering is a recently proposed arti€cial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically modeled through recurrent neural networks. While the requirement for modeling images is similar to traditional computer vision tasks, such as object ...

As it is simple and convenient to operate face recognition system, and this kind of system is without invasive, making face recognition technology become an important research direction of biometric identification. Face recognition technology involves digital image processing, pattern recognition, computer vision, neural networks and other research areas, has important research values. PCA algo...

Based on the information processing functionalities of spiking neurons, hierarchical spiking neural networks are proposed to simulate visual attention. Using spiking neural networks inspired by the visual system, an image can be decomposed into multiple visual image components. Based on specific visual image components and image features, a visual attention system is proposed to extract attenti...

In this paper, a technique employing artifkial neural networks for post-processing block coded images is presented. Visually important image features are extracted from the decompressed image and used as input to a feedforward neural network. The neural network learns to reconstruct the difference image between the original (uncompressed) and the decompressed image. Coding artifact reduction is...

  Purpose: Different views of an individuals’ image may be required for proper face recognition.   Recently, discrete cosines transform (DCT) based method has been used to synthesize virtual   views of an image using only one frontal image. In this work the performance of two different   algorithms was examined to produce virtual views of one frontal image.   Materials and Methods: Two new meth...

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