A Comparison of Hand-Geometry Recognition Methods Based on Low- and High-Level Features

This paper compares the performance of hand-geometry recognition based on high-level features and on low-level features. The difference between high- and low-level features is that the former are based on interpreting the biometric data, e.g. by locating a finger and measuring its dimensions, whereas the latter are not. The low-level features used here are landmarks on the contour of the hand. The high-level features are a standard set of geometrical features such as widths and lengths of fingers and angles, measured at preselected locations

Quantum Gates and Memory using Microwave Dressed States

Trapped atomic ions have been successfully used for demonstrating basic elements of universal quantum information processing (QIP). Nevertheless, scaling up of these methods and techniques to achieve large scale universal QIP, or more specialized quantum simulations remains challenging. The use of easily controllable and stable microwave sources instead of complex laser systems on the other hand promises to remove obstacles to scalability. Important remaining drawbacks in this approach are the use of magnetic field sensitive states, which shorten coherence times considerably, and the requirement to create large stable magnetic field gradients. Here, we present theoretically a novel approach based on dressing magnetic field sensitive states with microwave fields which addresses both issues and permits fast quantum logic. We experimentally demonstrate basic building blocks of this scheme to show that these dressed states are long-lived and coherence times are increased by more than two orders of magnitude compared to bare magnetic field sensitive states. This changes decisively the prospect of microwave-driven ion trap QIP and offers a new route to extend coherence times for all systems that suffer from magnetic noise such as neutral atoms, NV-centres, quantum dots, or circuit-QED systems.Comment: 9 pages, 4 figure

Designing Gabor windows using convex optimization

Redundant Gabor frames admit an infinite number of dual frames, yet only the canonical dual Gabor system, constructed from the minimal l2-norm dual window, is widely used. This window function however, might lack desirable properties, e.g. good time-frequency concentration, small support or smoothness. We employ convex optimization methods to design dual windows satisfying the Wexler-Raz equations and optimizing various constraints. Numerical experiments suggest that alternate dual windows with considerably improved features can be found

Perception and recognition of faces in adolescence

Most studies on the development of face cognition abilities have focussed on childhood, with early maturation accounts contending that face cognition abilities are mature by 3–5 years. Late maturation accounts, in contrast, propose that some aspects of face cognition are not mature until at least 10 years. Here, we measured face memory and face perception, two core face cognition abilities, in 661 participants (397 females) in four age groups (younger adolescents (11.27–13.38 years); mid-adolescents (13.39–15.89 years); older adolescents (15.90–18.00 years); and adults (18.01–33.15 years)) while controlling for differences in general cognitive ability. We showed that both face cognition abilities mature relatively late, at around 16 years, with a female advantage in face memory, but not in face perception, both in adolescence and adulthood. Late maturation in the face perception task was driven mainly by protracted development in identity perception, while gaze perception abilities were already comparatively mature in early adolescence. These improvements in the ability to memorize, recognize and perceive faces during adolescence may be related to increasing exploratory behaviour and exposure to novel faces during this period of life

Indonesian ID Card Recognition using Convolutional Neural Networks

Indonesian ID Card can be used to recognize citizen of Indonesia identity in several requirements like for sales and purchasing recording, admission and other transaction processing systems (TPS). Current TPS system used citizen ID Card by entering the data manually that means time consuming, prone to error and not efficient. In this research, we propose a model of citizen id card detection using state-of-the-art Deep Learning models: Convolutional Neural Networks (CNN). The result, we can obtain possitive accuracy citizen id card recognition using deep learning. We also compare the result of CNN with traditional computer vision techniques

A Comparison Of Performance On Two Adolescent Language Tests

The purpose of this study was to examine the relationship of performance on the "Fullerton Language Test for Adolescents" (FLTA) and the "Clinical Evaluation of Language Functions" (CELF). In addition, performance on these two language tests was compared to academic grades and achievement as measured by the "California Achievement Test" (CAT) . . . (the) results appeared to indicate that students attained higher performance on achievement tests and academic grades than their performance on adolescent language tests would suggest. On the basis of these findings, it appeared that students performed differently on the two adolescent language tests, an achievement test, and academic grades

A Theory of Finite Topology and Image Processing

Article信州大学工学部紀要 69: 11-24 (1991)departmental bulletin pape

Development of Alternative Fuel Briquettes from Poultry Processing Waste (Collecting, Storage and Handling)

The use of poultry processing plant waste as biomass energy resource could reduce dependence on the conventional fuels like coal, oil and gas. However, if it is not managed properly, it could give adverse impact to society and environment as it contains pathogenic organism, an infectious agent that can cause disease. So, the major concern is to handle the poultry processing waste appropriately without the expense of safety and health