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Despite of advancement in face recognition, it has received much more attention in last few decades in the field of research and in commercial markets this project proposes an efficient technique for face recognition system based on Deep Learning using Convolutional Neural Network (CNN) with Dlib face alignment. The paper describes the process involved in the face recognition like face alignment and...
Even though there has been enormous research in facial analysis and more sophisticated algorithm, face recognition fails drastically in real time when the facial images are occluded. This paper explains the algorithm and technical concepts behind the high accurate face recognition systems for a 2D frontal images with occlusion for a business requirments. Face recognition is implemented using Convolutional...
General game playing has emerged, in recent years, as a challenging testbed for artificial intelligence research. The premise is to build game players that are able to play any game without prior knowledge about the game. The purpose of this paper is to give an overview of the open problems in the current form of general game playing, along with a short survey of work already done. We also provide...
In this paper we discussed and implemented Morphological method for face recognition using fiducial points. A new technique for extracting facial features is suggested here. This method is independent of the face expressions. In recognition process, these fiducial point are fed as inputs to a Back propagation neural network for learning and identifying a person. So with the help of this technique,...
In this paper, we present a novel approach to group fingerprints according to its minutiae point's locations. Our technique for grouping fingerprints is based on the ART1 neural network. We compare the quality of clustering of our ART1 based clustering technique with that of the self organizing neural network (SOM) clustering algorithm in terms of intra-cluster distances. Our results show that the...
Three-dimensional ultrasound is emerging as a viable resource for the imaging of internal organs. Quantitative studies correlating ultrasonic volume measurements with MRI data continue to validate this modality as a more efficient alternative for 3D imaging studies. However, the processing required to form 3D images from a set of 2D images may result in a loss of spatial resolution and may give rise...
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