Search results for "artificial intelligence"
showing 10 items of 6122 documents
Verification of Symbolic Distributed Protocols for Networked Embedded Devices
2020
The availability of versatile and interconnected embedded devices makes it possible to build low-cost networks with a large number of nodes running even complex applications and protocols in a distributed manner. Common tools used for modeling and verification, such as simulators, present some limitations as application correctness is checked off-board and only focuses on source code. Execution in the real network is thus excluded from the early stages of design and verification. In this paper, a system for modeling and verification of symbolic distributed protocols running on embedded devices is introduced. The underlying methodology is rooted in a symbolic programming paradigm that makes …
A Study on Classification Methods Applied to Sentiment Analysis
2013
Sentiment analysis is a new area of research in data mining that concerns the detection of opinions and/or sentiments in texts. This work focuses on the application and the comparison of three classification techniques over a text corpus composed of reviews of commercial products in order to detect opinions about them. The chosen domain is about "perfumes", and user opinions composing the corpus are written in Italian language. The proposed approach is completely data-driven: a Term Frequency / Inverse Document Frequency (TFIDF) terms selection procedure has been applied in order to make computation more efficient, to improve the classification results and to manage some issues related to t…
Entropy-based Localization of Textured Regions
2011
Appearance description is a relevant field in computer vision that enables object recognition in domains as re-identification, retrieval and classification. Important cues to describe appearance are colors and textures. However, in real cases, texture detection is challenging due to occlusions and to deformations of the clothing while person's pose changes. Moreover, in some cases, the processed images have a low resolution and methods at the state of the art for texture analysis are not appropriate. In this paper, we deal with the problem of localizing real textures for clothing description purposes, such as stripes and/or complex patterns. Our method uses the entropy of primitive distribu…
Embedded Coprocessors for Native Execution of Geometric Algebra Operations
2016
Clifford algebra or geometric algebra (GA) is a simple and intuitive way to model geometric objects and their transformations. Operating in high-dimensional vector spaces with significant computational costs, the practical use of GA requires dedicated software and/or hardware architectures to directly support Clifford data types and operators. In this paper, a family of embedded coprocessors for the native execution of GA operations is presented. The paper shows the evolution of the coprocessor family focusing on the latest two architectures that offer direct hardware support to up to five-dimensional Clifford operations. The proposed coprocessors exploit hardware-oriented representations o…
Real-Time Body Gestures Recognition Using Training Set Constrained Reduction
2017
Gesture recognition is an emerging cross-discipline research field, which aims at interpreting human gestures and associating them to a well-defined meaning. It has been used as a mean for supporting human to machine interaction in several applications of robotics, artificial intelligence, and machine learning. In this paper, we propose a system able to recognize human body gestures which implements a constrained training set reduction technique. This allows the system for a real-time execution. The system has been tested on a publicly available dataset of 7,000 gestures, and experimental results have highlighted that at the cost of a little decrease in the maximum achievable recognition ac…
A Programmable Networked Processing Node for 3D Brain Vessels Reconstruction
2011
Real-time 3D imaging represents a developing trend in medical imaging. However, most of the 3D medical imaging algorithms are computationally intensive. In this paper, a programmable networked node for 3D brain vessels reconstruction is proposed. Starting from 2D PC-MRA (Phase-Contrast Magnetic Resonance Angiography) sequences, the node is able to generate the 3D brain vasculature using the MIP (Maximum Intensity Projection) algorithm. The node has been prototyped on the Celoxica RC203E board, equipped with a Virtex II FPGA, to get the advantages of an hardware implementation, reaching a better throughput with respect to analogous software implementations. Its generality and programmable ca…
Saliency Based Image Cropping
2013
Image cropping is a technique that is used to select the most relevant areas of an image, discarding the useless ones. Handmade selection, especially in case of large photo collections, is a time consuming task. Automatic image cropping techniques may help users, suggesting to them which part of the image is the most relevant, according to specific criteria. We suppose that the most visually salient areas of a photo are also the most relevant ones to the users. In this paper we present an extended version of our previously proposed method, to extract the saliency map of an image, which is based on the analysis of the distribution of the interest points of the image. Three different interest…
Embedded Knowledge-based Speech Detectors for Real-Time Recognition Tasks
2006
Speech recognition has become common in many application domains, from dictation systems for professional practices to vocal user interfaces for people with disabilities or hands-free system control. However, so far the performance of automatic speech recognition (ASR) systems are comparable to human speech recognition (HSR) only under very strict working conditions, and in general much lower. Incorporating acoustic-phonetic knowledge into ASR design has been proven a viable approach to raise ASR accuracy. Manner of articulation attributes such as vowel, stop, fricative, approximant, nasal, and silence are examples of such knowledge. Neural networks have already been used successfully as de…
Normalised compression distance and evolutionary distance of genomic sequences: comparison of clustering results
2009
Genomic sequences are usually compared using evolutionary distance, a procedure that implies the alignment of the sequences. Alignment of long sequences is a time consuming procedure and the obtained dissimilarity results is not a metric. Recently, the normalised compression distance was introduced as a method to calculate the distance between two generic digital objects and it seems a suitable way to compare genomic strings. In this paper, the clustering and the non-linear mapping obtained using the evolutionary distance and the compression distance are compared, in order to understand if the two distances sets are similar.
360° Tracking Using a Virtual PTZ Camera
2017
Object tracking using still or PTZ cameras is a hard task for large spaces and needs several devices to completely cover the area or to track multiple subjects. The introduction of \(360^{\circ }\) camera technology offers a complete view of the scene in a single image and can be useful to reduce the number of devices needed in the tracking problem. In this paper we present a framework using \(360^{\circ }\) cameras to simulate an unlimited number of PTZ cameras and to be used for tracking. The proposed method to track a single target process an equirectangular view of the scene and obtains a model of the moving object in the image plane. The target is tracked analyzing the next frame of th…