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The maintenance of static standing balance is not only essential for performing everyday activities but is also an important risk factor for prediction of falls in the elderly adults. Human balance / posture control is controlled by complex integration of different senses. The changes in steadiness of balance can be characterized by center-of-pressure (COP) signals measured from a 3-D force plate...
In this paper, we study the performance of different classifiers on the CIFAR-10 dataset, and build an ensemble of classifiers to reach a better performance. We show that, on CIFAR-10, K-Nearest Neighbors (KNN) and Convolutional Neural Network (CNN), on some classes, are mutually exclusive, thus yield in higher accuracy when combined. We reduce KNN overfitting using Principal Component Analysis (PCA),...
Cascade-Forward Neural Network (CFNN) performance is explored in this paper for blood stain image analysis. The blood stain images of various size, shape and impact angles are captured through experimentation. Each blood stain in the image is first detected using sobel edge detector. After the image has been thresholded and the noise removed, geometric properties of the blood drop is measured with...
Breast cancer is one from various diseases that has got great attention in the last decades. This due to the number of women who died because of this disease. Segmentation is always an important step in developing a CAD system. This paper proposed an automatic segmentation method for the Region of Interest (ROI) from breast thermograms. This method is based on the data acquisition protocol parameter...
Iris recognition is gaining more attention and the development of the field is increasing rapidly. This paper presents a complete iris recognition system. The iris features are obtained using Speeded Up Robust Features (SURF) after enhancing the image using Contrast Limited Adaptive Histogram Equalization (CLAHE). A novel matching algorithm based on applying fusion rules at different levels is proposed...
This paper presents a technique inspired by swarm methodologies such as ant colony algorithms for processing simple and complicated images. It is shown that the proposed technique for image processing is capable of performing feature extraction for edge detection and segmentation, even in the presence of noise. Our proposed approach, Ant-based Correlation for Edge Detection (ACED), is tested on different...
This paper presents a smart and simple algorithm for vehicle's license plate recognition system. The proposed algorithm consists of three major parts namely detection of license plate from an image, segmentation and recognition of characters. For detection of the license plate, a memory and speed proficient algorithm has been proposed. After detection, statistical based template matching is used for...
The detection of driving space is the most fundamental step in intelligent vehicle control. This research paper proposes a generic vision based algorithm for identifying driving surfaces in various indoor and outdoor environments. In this paper, instead of relying on a static model for demarcating the boundaries of the driving surfaces, we propose a novel algorithm that provides an adaptive method...
Intrusion detection is one of the most challenging problems in network security. Detection of attacks on a particular network is not an easy task. Since recently, several machine learning, pattern classification and evolutionary techniques have been used on KDD99Cup dataset for detecting different kinds of intrusions that exist in the dataset. In this paper, we present a genetic algorithm (GA)-based...
In this paper, we propose a framework that fuses multiple features for improved action recognition in videos. The fusion of multiple features is important for recognizing actions as often a single feature based representation is not enough to capture the imaging variations (view-point, illumination etc.) and attributes of individuals (size, age, gender etc.). Hence, we use two types of features: i)...
The typical optical character recognition (OCR) systems, regardless the characterpsilas nature, are based mainly on three stages, preprocessing, features extraction and discrimination (recognizer). Each stage has its own problems and effects on the system efficiency such as time consuming and recognition errors. In order to avoid these difficulties this research paper presents new construction of...
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