Aun Irtaza

In this paper a Neural Network based architecture for content based image retrieval is presented which is based on the concept of in-depth texture analysis of images. Expand

A bandelet transform based image representation technique is presented in this paper, which reliably returns the information about the major objects found in an image. Expand

We propose a framework that detects falls by using acoustic Local Ternary Patterns (acoustic-LTPs) by analyzing environmental sounds. Expand

We have combined genetic algorithm and support vector machines to reduce the existing gap between high-level semantic content of the images and the information provided by their low-level descriptors. Expand

We proposed a novel technique to precisely detect the various stages of the diabetic retinopathy by extending the research of the content-based image retrieval domain. Expand

A deep region based convolutional neural network (RCNN) is proposed for automated Melanoma region segmentation using dermoscopic images to overcome the challenges of automatedMelanoma segmentation within dermatological images. Expand

This paper presents a viable multimodal feature-level fusion approach for robust human action recognition, which utilizes data from multiple sensors, including RGB camera, depth sensor, and wearable inertial sensors. Expand

The most common image tampering often for malicious purposes is to copy a region of the same image and paste to hide some other region. Expand

The elderly people living alone or life of a patient face distress situations particularly in case of falling and becoming unable to ask for help. Expand