The artificialneuralnetworks (ANNs) have been used successfully in applications such as pattern recognition, imageprocessing, automation and control. Majority of today's applications use backpropagate feedforwa...
详细信息
The artificialneuralnetworks (ANNs) have been used successfully in applications such as pattern recognition, imageprocessing, automation and control. Majority of today's applications use backpropagate feedforward ANN. In this paper, two methods of P pattern L layer ANN learning on n x n RMESH have been presented. One required memory space of O(nL) but conceptually is simpler to develop and the other uses pipelined approach which reduces the memory requirement to O(L). Both of these algorithms take O(PL) time and are optimal for RMESH architecture. (C) 1998 Elsevier Science B.V. All rights reserved.
artificialneural network models are becoming very attractive in imageprocessing where high computational performance and parallel architectures are required. Recently, many papers appeared on applications of neural ...
详细信息
artificialneural network models are becoming very attractive in imageprocessing where high computational performance and parallel architectures are required. Recently, many papers appeared on applications of neuralnetworks to problems where some degree of intelligence or human-like performance is desired. This paper describes a novel neural network architecture for image recognition and classification. The proposed neural network, called an image recognition neural network (IRNN), is designed to recognize an object or to estimate an attribute of an object. IRNN takes an analog gray level image as an input and produces an appropriate recognition code at the output.
In this paper(1), we investigate several fusion techniques for designing a composite classifier to improve the performance (probability of correct classification) of FLIR ATR. The motivation behind the fusion of ATR a...
详细信息
ISBN:
(纸本)0819444081
In this paper(1), we investigate several fusion techniques for designing a composite classifier to improve the performance (probability of correct classification) of FLIR ATR. The motivation behind the fusion of ATR algorithms is that if each contributing technique in a fusion algorithm (composite classifier) emphasizes on learning at least some features of the targets that are not learned by other contributing techniques for making a classification decision, a fusion of ATR algorithms may improve overall probability of correct classification of the composite classifier. In this research, we propose to use four ATR algorithms for fusion. We propose to use averaged Bayes classifier, committee of experts, stacked-generalization, winner-takes-all, and ranking-based fusion techniques for designing the composite classifiers. The experimental results show an improvement of more than 5 % over the best individual performance.
Pulse Coupled neuralnetworks have been extended and modified to suit image segmentation applications. Previous research demonstrated the ability of a PCNN to ignore noisy variations in intensity and small spatial dis...
详细信息
Pulse Coupled neuralnetworks have been extended and modified to suit image segmentation applications. Previous research demonstrated the ability of a PCNN to ignore noisy variations in intensity and small spatial discontinuities in images that prove beneficial to image segmentation and image smoothing. This paper describes four research and development projects that relate to PCNN segmentation - three different digital imageprocessingapplications and a CMOS integrated circuit implementation. The software for the diagnosis of Pulmonary Embolism from VQ lung scans uses PCNN in single burst mode for segmenting perfusion and ventilation images. The second project is attempting to detect ischemia by comparing 3-D SPECT (Single Photon Emission Computed Tomography) images of the heart obtained during stress and rest conditions, respectively. The third application is a space science project which deals with the study of global aurora images obtained from Ultraviolet imager (UVI). The paper also describes the hardware implementation of PCNN algorithm as an electro-optical chip.
Solid waste recycling is more and more increasing according to the need to realize dismantled material recovery and to reduce overall environmental pollution. When a recycling strategy is applied sorting strategies ha...
详细信息
ISBN:
(纸本)0819444081
Solid waste recycling is more and more increasing according to the need to realize dismantled material recovery and to reduce overall environmental pollution. When a recycling strategy is applied sorting strategies have to be developed and implemented. Such an approach ca be considered as the second logical step of the process that is, after that the attributes (physical, chemical, morphological, morphometrical, textural, etc.) of the materials resulting from classical processing (comminution, classification, separation, etc.) are detected and numerically modeled. The resulting feature vector need to be "handled" by a software architecture performing the required recognition/classification procedure and defining the quality of the investigated products. From the results further "feed-back" or "feed-forward" control strategies can be applied in order to improve equipment or processing architectures performances. In this paper are analyzed and described neural network based sorting strategies applied with reference to fluff (light fraction of the materials resulting from car dismantling) recognition.
Regularization is a paradigm for performing image segmentation and edge detection, that can be implemented in a neural network type architecture. Various topics and problems pertaining to the use of regularization for...
详细信息
ISBN:
(纸本)0819408743
Regularization is a paradigm for performing image segmentation and edge detection, that can be implemented in a neural network type architecture. Various topics and problems pertaining to the use of regularization for imageprocessingapplications are discussed. Topics include data fusion, sensor blur, and the operation on partitioned images. A mathematical analysis of the different topics is presented, including a modification of the original regularization energy functional to perform data fusion.
Cellular neuralnetworks (CNNs) are well suited for imageprocessing due to the possibility of a parallel computation. In this paper, we present two algorithms for tracking and obstacle avoidance using CNNs. Furthermo...
详细信息
Cellular neuralnetworks (CNNs) are well suited for imageprocessing due to the possibility of a parallel computation. In this paper, we present two algorithms for tracking and obstacle avoidance using CNNs. Furthermore, we show the implementation of an autonomous robot guided using only real-time visual feedback;the imageprocessing is performed entirely by a CNN system embedded in a digital signal processor (DSP). We successfully tested the two algorithms on this robot. Copyright (c) 2006 John Wiley & Sons, Ltd.
Selective application of herbicide to weeds at an early stage in crop growth is an important aspect of site-specific management of field crops, both economically and environmentally. This paper describes the applicati...
详细信息
Selective application of herbicide to weeds at an early stage in crop growth is an important aspect of site-specific management of field crops, both economically and environmentally. This paper describes the application of a neural network classifier to differentiate between 2 and 3 weeks old sunflower plants and common cocklebur weeds of similar size, shape and colour. Colour images were obtained by a digital camera, in natural sunlight. A specific objective was to minimise the subsequent imageprocessing operations needed to enhance the images and to extract the features needed by a back propagation neural network classifier. neural network structures with different numbers of hidden layers and neurons in them were tested to find the optimal classifier. The maximum number of correctly recognised images in distinguishing weeds from sunflower plants was 71 (out of 86), while it was 82 and 74 in separating sunflower and weed images from bare soil images, respectively. (C) 2004 Elsevier B.V. All rights reserved.
This paper presents a 3-D reconstruction method IBM(image based modeling) of an image that does not contain any camera information. This system adopts a 3D reconstruction method based on a model. Model-based 3D recons...
详细信息
ISBN:
(纸本)081944815X
This paper presents a 3-D reconstruction method IBM(image based modeling) of an image that does not contain any camera information. This system adopts a 3D reconstruction method based on a model. Model-based 3D reconstruction recovers an image using the geometric characteristics of a pre-defined polyhedron model. It uses a pre-defined polyhedron model as the primitive and the 3D reconstruction is processed by mapping the correspondence point of the primitive model onto the picture image. Existing model-based 3D reconstruction methods were used for the reconstruction of camera parameters or error method through iteration. However, we proposed a method for a primitive model that uses the segment and the center of the segment for the reconstruction process. This method enables the reconstruction of the primitive model to be processed using the minimum camera parameters (e.g. focal length) during the segment reconstruction process.
In this paper a novel method of estimating displacement of moving objects from one frame to the next in the image sequence is presented. This method is based on using the artificialneuralnetworks for different model...
详细信息
ISBN:
(纸本)0819425842
In this paper a novel method of estimating displacement of moving objects from one frame to the next in the image sequence is presented. This method is based on using the artificialneuralnetworks for different models of motion. The two model is examined: affine flow and planar surface motion. Various circuit architectures of simple neuron-like processors are considered for estimation of motion parameters. The efficiency of the proposed networks are investigated by computer simulation for using in video processing.
暂无评论