Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services Abstract?Ubiquitous Data Accessing Method in IoT-Based Information System for Emergency Medical Services.The rapid development of Internet of things (IoT) technology makes it possible for connecting various smart objects together through the Internet and providing more data interoperability methods for application purpose. Recent research…
Ultra-Low Power, Highly Reliable, and Nonvolatile Hybrid MTJ/CMOS Based Full-Adder for Future VLSI Design Abstract– Very large-scale integrated circuit (VLSI) design, based on today?s CMOS technologies, are facing various challenges. Shrinking transistor dimensions, reduction in threshold voltage, and lowering power supply voltage, cause new concerns such as high leakage current, and increase in radiation sensitivity….
Ultralow-Voltage High-Speed Flash ADC Design Strategy Based on FoM-Delay Product Abstract? The ultralow-voltage (ULV) design strategy for high-speed flash analog-to-digital converters (ADCs). A lower supply voltage decreases the energy consumption at the cost of conversion speed. A new index, the figure-of-merit (FoM)-delay (FD) product, is introduced to provide a balance between the energy efficiency and…
Ultrasound Image Denoising using a Combination of Bilateral Filtering and Stationary Wavelet Transform Abstract?Abstract Medical image degradation has a significant impact on image quality, and thus affects human interpretation and the accuracy of computer-assisted diagnostic techniques.Unfortunately, Ultrasound images are mainly degraded by an intrinsic noise called speckle. Therefore, despekle filtering is a critical preprocessing step…
Uncertain Data Clustering in Distributed Peer-to-Peer Networks Abstract-In general, Uncertain data clustering has been recognized as an essential task in the research of data mining. Many centralized clustering algorithms are extended by defining new distance or similarity measurements to tackle this issue. With the fast development of network applications, these centralized methods show their limitations…
Underwater Image Restoration based on Image Blurriness and Light Absorption Abstract?Abstract Underwater images often suffer from color distortion and low contrast because light is scattered and absorbed when traveling through water. Such images with different color tones can be shot in various lighting conditions, making restoration and enhancement difficult. We propose a depth estimation method…
Unified VLSI architecture for photo core transform used in JPEG XR Abstract? In JPEG XR image compression technique the unified photo core transform is used. It is designed to support high dynamic range and high definition formats thus this type of JPEG XR image compression with unified photo core transform is widely used in real…
Unprivileged Black-Box Detection of User-Space Keyloggers Abstract?Software keyloggers are a fast growing class of invasive software often used to harvest confidential information. One of the main reasons for this rapid growth is the possibility for unprivileged programs running in user space to eavesdrop and record all the keystrokes typed by the users of a system.<...
Unraveling the Effect of Textured Contact Lenses on Iris Recognition Abstract?Unraveling the Effect of Textured Contact Lenses on Iris Recognition. The presence of a contact lens, particularly a textured cosmetic lens, poses a challenge to iris recognition as it obfuscates the natural iris patterns. The main contribution of this paper is to present an in-depth…
Unsupervised Colour Image Segmentation using Dual-tree Complex Wavelet Transform Abstract?a novel image segmentation technique for noisy colour images, in which the heavy-tailed characteristics of the image are modelled by Cauchy distributions. First, the RGB colour bands of the noisy image are decomposed into multiresolution representations using the dual-tree complex wavelet transform.< Final Year Project >…
Unsupervised Deep Feature Extraction for Remote Sensing Image Classification Abstract? The use of single layer and deep convolutional networks for remote sensing data analysis. Direct application to multi- and hyper-spectral imagery of supervised (shallow or deep) convolutional networks is very challenging given the high input data dimensionality and the relatively small amount of available labelled…
Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammo graphic Risk Scoring Abstract?Mammo graphic risk scoring has commonly been automated by extracting a set of handcrafted features from mammograms, and relating the responses directly or indirectly to breast cancer risk. We present a method that learns a feature hierarchy from unlabeled data. < final...
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