Breast cancer is the main death rate from malignant growth worldwide and most frequently diagnosed type of in females. Machine learning systems have been developed to assist accurate detection cancer. There are numerous methods for detection. But histopathological images thought be more precise. In this study, we used HOG features extractor extract statistical histopathology invasive ductal car...

Humans can perform an enormous number of actions like running, walking, pushing, and punching, them in multiple ways. Hence recognizing a human action from video is challenging task. In supervised learning environment, are first represented using robust features then classifier trained for classification. The selection does affect the performance recognition. This work focuses on comparison two...

Computer vision enables a wide range of applications in robotics/drones, self-driving cars, smart Internet of Things, and portable/wearable electronics. For many of these applications, local embedded processing is preferred due to privacy and/or latency concerns. Accordingly, energy-efficient embedded vision hardware delivering real-time and robust performance is crucial. While deep learning is...

The deformable parts model (DPM) [6] serves as a key component in most modern state-of-the-art object detection systems. At a high level, the DPM composes a single object model by learning to detect and assemble parts of an object. Most modern systems employing the DPM employ densely computed Histogram of Oriented Gradients [5] features at training time. Despite the success of HOG features in m...

In this supplementary material we show a full derivation of our Reduced Ensemble of Correlation Filters and provide more quantitative results that are not shown in the paper due to space constraints. 1 Ensemble of Exemplar Classifiers for Pose-by-Detection 1.1 Exemplar Correlation Filters Exemplar classifiers are suited to the task of pose-by-detection. For each one of the V viewpoint renders w...

Automated banknote recognition systems are essential for people with visual impairments who face challenges distinguishing between different currency denominations. This study presents a novel method aimed at helping blind identify banknotes from three countries (Egypt, Saudi Arabia, and the United States of America) by using proposed feature detection algorithm. Our system has two main stages:...