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Many existing issues pertaining to power sector such as-demand response management, theft detection, outage management etc. can be solved efficiently with grid modernization. Out of these, demand response is one such issue which affects the overall grid stability. One way of managing demand response is to balance the load in smart grid (SG). In this paper, a novel scheme for handling the demand response...
Self-tracking of food intake has been studied at length, but many challenges still remain. Current systems often require significant effort from users, and work that has tried to reduce it resulted in low accuracy or delays. Effort is a major barrier to long term use of self-tracking systems. We propose CalNag, a system that integrates a weighing scale, a barcode reader, and a cloud based service...
In the present work, reliability of the software Mirtoolbox that was developed for music signal processing has been investigated into. Motivation for the work stems from the fact that performance report of the software is not available in the literature from sources other than the developers of the software. A few functions available in the software for extraction of some basic musical features have...
This paper presents an evaluation of two dense descriptors that have been or can be used in face recognition. Local Binary Pattern (LBP) is an established descriptor with many researchers focusing on its utility in Face Recognition. Local Tetra Patterns (LTrP) have been recently introduced and this paper explores the possibility of its utility in Face Recognition. A comparative analysis on the use...
Given a set of historic good traces, trace-based anomaly detection deals with the problem of determining whether or not a specific trace represents a normal execution scenario. Most current approaches mainly focus on application areas outside of the embedded systems domain and thus do not take advantage of the intrinsic properties of this domain. This work introduces SiPTA, a novel technique for offline...
We present a novel approach to localizing parts in images of human faces. The approach combines the output of local detectors with a nonparametric set of global models for the part locations based on over 1,000 hand-labeled exemplar images. By assuming that the global models generate the part locations as hidden variables, we derive a Bayesian objective function. This function is optimized using a...
We present two novel methods for face verification. Our first method - “attribute” classifiers - uses binary classifiers trained to recognize the presence or absence of describable aspects of visual appearance (e.g., gender, race, and age). Our second method - “simile” classifiers - removes the manual labeling required for attribute classification and instead learns the similarity of faces, or regions...
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