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The following topics are dealt with: vehicle detection; discrete time queueing system; CBMLAD; linear programming model; surface water quality assessment; fuzzy subgroups; computer aided optimum design; aerodynamic modeling; fuzzy logic controller; adaptive neural network; trajectory planning; nurbs model; XML data safety; sparse signal estimation; condition monitoring information model; ECG extraction;...
It is known that detecting small targets in remotely sensed image is difficult and challenging work. Filter neural network is designed to detect target which based morphological, structure element is used as network parameter, by competition and cooperation, network parameter is adjusted. Morphologic changed-weight neural network algorithm is used to realize small infrared target detection under complex...
This paper proposed a new motion detection algorithm based on neural network (NN). Video background was modeled by combing probabilistic neural network (PNN) and winner take all (WTA) network, which is called adaptive background PNN (ABPNN). Every pixel in a video frame was classified to be foreground or background by conditional probability of being a background. Foreground was further classified...
Mammograms can depict most of the significant changes of breast disease. The primary radiographic signs of cancer are masses (its density, site, shape, borders), spicular lesions and calcification content.These features may be extracted using various detection system .The common are Neural network, wavelet, fuzzy logic, evolutionary approach and finally hybrid system ,which employs integration of...
The detection of texts in video images is an important task towards automatic content-based information indexing and retrieval system. In this paper, we propose a texture-based method for text detection in complex video images. Taking advantage of the desirable characteristic of gray-scale invariance of local binary patterns (LBP), we apply a modified LBP operator to extract feature of texts. A polynomial...
In order to decrease negative effects brought by the particularity and complexity of imaging environment, and satisfy the real-time need of the underwater task, combined invariant moments are extracted as recognition features. Furthermore, an underwater target recognition system based on neural network which improved by Artificial Fish Swarm Algorithm (AFSA) is proposed. AFSA is of capable of attaining...
Developing robust computer vision algorithms to detect fruit in trees is challenging due to less controllable conditions, including variation in illumination within an image as well as between image sets. There are two classes of techniques: local-feature-based techniques and shape-based techniques, which have been used extensively in this application domain. Out of the two classes, the local-feature-based...
In this paper, a stereo framework for a robust real time localization of objects using networkpsilas camera pairs is presented. The stereo system contains a combination of static and pan-tilt-zoom (PTZ) cameras instead of traditional dual head mounted cameras. The proposed novelty consists in applying stereo vision to heterogeneous cameras belonging to a video-surveillance network. First, a look-up-table...
Detecting vehicles from video sequence is very challenging due to the wide varieties of vehicle appearances and the complexity of the backgrounds. At present, many algorithms in the image recognition have a narrow applicability and a weak real-time. Aiming at this problem, a recognition method which was combined by features extraction using Gabor wavelet and BP neural network algorithm for the classification...
We have proposed a complete system for text detection and localization in gray scale scene images. A boosting framework integrating feature and weak classifier selection based on computational complexity is proposed to construct efficient text detectors. The proposed scheme uses a small set of heterogeneous features which are spatially combined to build a large set of features. A neural network based...
An improved, intelligent pedestrian counting system, using images obtained from a single video camera, is described in this paper. This system is capable of detecting and counting a group of pedestrians in the region of interest. Groups can be extracted by using the image processing method, and a kernel-induced probabilistic neural network (KPNN) employed to perform the classification, and estimate...
The demand for reliable traffic sign recognition (TSR) increases with the development of safety driven advanced driver assistance systems (ADAS). Emerging technologies like brake-by-wire or steer-by-wire pave the way for collision avoidance and threat identification systems. Obviously, decision making in such critical situations requires high reliability of the information base. Especially for comfort...
This paper presents a new neural network to perform the visual pattern classification task. The neural network is called I-PyraNet which is a hybrid implementation of the PyraNet and the concepts of the inhibitory fields. In order to improve the results obtained by this neural network, it is also presented the 2-D Gabor filter. Furthermore, both, the neural network and the filter, are applied over...
The vision has many sensors responsible for capturing information that is sent to the brain. The gaze reflects its attention, intention and interest of the brain towards the outside world. Therefore, the detection of the gaze direction is a promising alternative for the simulation programs, virtual reality applications and human-machine special communication. Cheaper devices to capture images and...
Object-based attention theory posits that attention is directed towards one object at a time. This paper attempts to simulate top-down influences. Five components of top-down influences are modeled: structure of object representation for long-term memory (LTM), learning of object representations, deduction of task-relevant features, estimation of top-down biases, mediation between bottom-up and top-down...
The paper deals with detection of steganography content. Steganography is an additional method in cryptography which helps to hide coded messages inside pictures or videos. To hide a message is very important but also revealing such content is important to avoid of usage by jailbirds. The revealing of steganography is not easy. This paper shows how neural networks are able to detect steganography...
Past work on face detection has emphasized the issues of feature extraction and classification, however, less attention has been given on the critical issue of feature selection. We consider the problem of face and non-face classification from frontal facial images using feature selection and neural networks. We argue that feature selection is an important issue in face and non-face classification...
In this paper, we address the problem of detecting and localizing cars in still images. The proposed car detection system is based on a hierarchical feature detector in which the processing units are shunting inhibitory neurons. To reduce the training time and complexity of the network, the shunting inhibitory neurons in the first layer are implemented as directional nonlinear filters, whereas the...
In this paper two fuzzy clustering algorithms, namely fuzzy C-means (FCM) and Gustafson Kessel clustering (GKC), have been used for detecting changes in multitemporal remote sensing images. Change detection maps are obtained by separating the pixel-patterns of the difference image into two groups. To show the effectiveness of the proposed technique, experiments are conducted on three multispectral...
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