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2009 Article Unknown

Adaptive committees of feature-specific classifiers for image classification
Fagni T., Falchi F., Sebastiani F.
Researchers from ISTI-CNR, Pisa, are working on the effective and efficient classification of images through a combination of adaptive image classifier committees and metric data structures explicitly devised for nearest neighbour searches.Source: ERCIM news 78 (2009): 41–41.

See at: CNR People


2008 Article Unknown

Efficient video-stream filtering
Falchi F., Gennaro C., Savino P., Stanchev P.
A new approach for video-stream filtering that makes use of the features representing video content and exploits the properties of metric spaces can help reduce the filtering receiver's computational load.Source: IEEE multimedia 15 (2008): 52–62. doi:10.1109/MMUL.2008.6
DOI: 10.1109/MMUL.2008.6

See at: DOI Resolver | ieeexplore.ieee.org | CNR People


2017 Article Unknown

Preface. Special Section on "Similarity Search and Applications: Selected Papers from SISAP 2015"
Amato G., Connor R., Falchi F., Gennaro C.
Source: Information systems (Oxf.) 64 (2017): 151–151. doi:10.1016/j.is.2016.10.008
DOI: 10.1016/j.is.2016.10.008

See at: DOI Resolver | CNR People | www.sciencedirect.com


2019 Article Open Access OPEN

About deep learning, intuition and thinking
Falchi F.
In recent years, expert intuition has been a hot topic within the discipline of psychology and decision making. The results of this research can help in understanding deep learning; the driving force behind the AI renaissance, which started in 2012.Source: ERCIM news (2019): 14–14.

See at: ISTI Repository Open Access | ercim-news.ercim.eu | CNR People


2011 Report Unknown

A1.1.1 Lo stato dell'arte: tecnologia ed utenti
Falchi Fabrizio, Ippolito Valentina, Loschiavo Domenico, Lucchese Claudio, Lungarotti Francesca, Melani, Alessio, Minelli, Sam, Pialli Saverio, Rossi Silvia, Salvadori Sauro, Scartoni Rita, Scopigno Roberto, Tavanti Francesca, La Torre Francesco, Venturini Rossano
This document reports the state of the art related to the technologies of interest of the VISITO Tuscany project

See at: CNR People


2013 Other Unknown

Visual information retrieval
Falchi F.
VIR is a library for content based image retrieval and classification based on global and local features. The library allows comparing images considering their global and/or local features. It includes local features matching, RANSAC, MPEG-7 global features comparisons, kNN classification, Bag-of-Words (or Bag-of-Features) approach. It is an ongoing project. At the moment it does not implement feature extraction.

See at: github.com | CNR People


2013 Article Unknown

Large scale image retrieval using vector of locally aggregated descriptors
Amato G., Bolettieri P., Falchi F., Gennaro C.
We propose using vectors of locally aggregated descriptors (VLAD) to address the problem of image search on a very large scale. We expect that this technique will overcome the quantization error problem faced in Bag-of-Words (BoW) representations.Source: ERCIM news 95 (2013): 36–37.

See at: ercim-news.ercim.eu | CNR People


2009 Conference object Unknown

Adaptive committees of feature-specific classifiers for image classification
Fagni T., Falchi F., Sebastiani F.
We present a system for image classification based on an adaptive committee of five classifiers, each specialized on classifying images based on a single MPEG-7 feature. We test four different ways to set up such a committee, and obtain important accuracy improvements with respect to a baseline in which a single classifier, working an all five features at the same time, is employed.Source: 2nd International Workshop on Image Mining Theory and Applications, pp. 113–122, Lisbon, PT, 7 febbraio 2009

See at: CNR People


2008 Report Unknown

Adaptive committees of feature-specific classifiers for image classification
Fagni T., Falchi F., Sebastiani F.
We present a system for image classification based on an adaptive committee of five classifiers, each specialized on classifying images based on a single MPEG-7 feature. We test four different ways to set up such a committee, and obtain important accuracy improvements with respect to a baseline in which a single classifier, working an all five features at the same time, is employed.

See at: CNR People


2006 Other Unknown

MILOS – Multimedia Content Management System
Rabitti F., Amato G., Savino P., Debole F., Bolettieri P., Falchi F.
MILOS is a multimedia content management system specialised to support multimedia digital library applications. MILOS provides applications with functionalities for the storage of arbitrary multimedia documents and their content based retrieval using arbitrary metadata models represented in XML. MILOS is flexible in the management of documents containing different types of data and content descriptions; it is efficient and scalable in the storage and content based retrieval of these documents.

See at: CNR People


2009 Report Unknown

SAPIR D5.4 - Executing complex similarity queries over multi layer P2P search structures
Falchi F., Batko M.
This deliverable reports the activities conducted within Task 5.4 "Executing complex similarity queries over multi layer P2P search structures" of the SAPIR project. In particular the deliverable discusses complex similarity queries issues and the implementation of the query processing over the P2P indexing. The document is accompanied by a zip file containing the javadoc for MUFIN.Source: Numero deliverableD5.4, 2009
Project(s): SAPIR

See at: CNR People


2011 Article Unknown

VISITO Tuscany: landmark recognition for cultural heritage
Amato G., Falchi F., Bolettieri P.
VISITO Tuscany (VIsual Support to Interactive TOurism in Tuscany) is a research project which investigates techniques for producing an interactive guide, accessible via smartphone, for tourists visiting cities of art. The system applies image analysis and content recognition techniques to recognize photographed monuments. The user just has to take a picture of a tourist landmark to obtain pertinent information on his or her smartphone.Source: ERCIM news 86 (2011): 22–23.

See at: CNR People


2012 Report Unknown

ASSETS - Scalable content-based indexing and ranking
Amato G., Bolettieri P., Falchi F., Lazaridis M., Paytuvi O., López F.
This is a technical document detailing the ASSETS architecture and APIs for "scalable content-based indexing and ranking" components. It introduces technical aspects of all the software services that have been defined, analyzed, implemented and tested during ASSETS WP2.2. This document provides the following information: . The software requirements overview; . The technical documentation (UML diagrams, services description and API documentation, the software packaging and installation); . The user manual.Project(s): ASSETS

See at: CNR People


2010 Report Unknown

VISITO - G3.1 Relazione avanzamento progetto VISITO Tuscany
Amato G., Falchi F., Bolettieri P., Lucchese C., Scopigno R., La Torre F., Minelli S., Tavanti F., Scartoni R., Salvadori S., Zanetti N., Loschiavo D.
Questo documento descrive i risultati ottenuti dal progetto VISITO-Tuscany nei primi otto mesi di lavoro. Dopo una breve panoramica degli obbiettivi generali del progetto, si evidenzieranno i risultati previsti alla fine dell'ottavo mese e si esporrà quale è stato il lavoro effettivamente sostenuto e i risultati raggiunti, in maniera dettagliata per le varie attività previste.Source: pp.1–35, 2010

See at: CNR People


2010 Report Unknown

VISITO Tuscany - Sviluppo componente per il matching approssimato di immagini
Amato G., Falchi F., Bolettieri P.
In this document, the developing of the software component for approximate image matching is reported. This document is an output of the Activity A4.1 "Strumenti per il matching approssimato delle immagini" of the VISITO Tuscany project. Planned from month 4 to month 12, the activity started earlier on month 3. The output of Activity 4.1 is this document and the software component made available inside on the VISITO Tuscany project wiki. The software component is optimized for working on images related to cultural heritage objects.

See at: CNR People


2015 Report Unknown

Smart Area CNR Pisa - Smart parking - Technical Report
Amato G., Carrara F., Falchi F., Gennaro C., Vairo C.
The Smart Parking application has the purpose of determining the number and the position of the available slots in the parking lot of the CNR Area in Pisa. To achieve this goal, nine smart cameras (video cameras with computational capabilities) are mounted on top of the roof in front of the parking to be monitored, and visual computing algorithms have been developed in order to recognize whether a parking slot is empty or occupied by a car.

See at: CNR People


2011 Report Unknown

VISITO Tuscany - Strumenti per la classificazione ed annotazione automatica delle immagini
Amato G., Falchi F., Bolettieri P.
In this document, the developing of the software component for approximate image matching is reported. This document is an output of the Activity A4.1 "Strumenti per il matching approssimato delle immagini" of the VISITO Tuscany project. Planned from month 4 to month 12, the activity started earlier on month 3. The output of Activity 4.1 is this document and the software component made available inside on the VISITO Tuscany project wiki. The software component is optimized for working on images related to cultural heritage objects.

See at: CNR People


2011 Report Unknown

VISITO Tuscany - Sviluppo componente per la ricerca efficiente e scalabile di immagini
Amato G., Bolettieri P., Falchi F., Gennaro C.
In this document, the developing of the software component for approximate image matching is reported. This document is an output of the Activity A4.3 "Indici efficienti per il matching approssimato e la classificazione delle immagini" of the VISITO Tuscany project. The output of Activity 4 .3 is this document and the software component made available inside on the VISITO Tuscany project wiki. The software component is optimized for working on images related to cultural heritage objects.

See at: CNR People


2016 Conference object Unknown

Indexing 100M images with deep features and MI-File
Amato G, Falchi F, Gennaro C, Rabitti F.
In the context of the Multimedia Commons initiative, we extracted and indexed deep features of about 100M images uploaded on Flickr between 2004 and 2014 and published under a Creative Commons commercial or noncommercial license. The extracted features and an online demo built using the MI-File approximated data structure are both publicly available. The online CBIR system demonstrates the effectiveness of the deep features and the efficiency of the indexing approach.Source: Italian Information Retrieval Workshop, Venezia, Italy, 30-31 May 2016

See at: ceur-ws.org | CNR People


2017 Report Open Access OPEN

Exploring epoch-dependent stochastic residual networks
Carrara F., Esuli A., Falchi F., Moreo Fernández A.
The recently proposed stochastic residual networks selectively activate or bypass the layers during training, based on independent stochastic choices, each of which following a probability distribution that is fixed in advance. In this paper we present a first exploration on the use of an epoch-dependent distribution, starting with a higher probability of bypassing deeper layers and then activating them more frequently as training progresses. Preliminary results are mixed, yet they show some potential of adding an epoch-dependent management of distributions, worth of further investigation.

See at: ISTI Repository Open Access | arxiv.org | CNR People