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Jean-François Molino

dblp:13/10071 · DBLP profile ↗
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4ranked-venue papers
0as first author
0since 2021 · last 2016
0000-0001-8853-7133ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 4

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%
Databases, data mining, and information retrieval
2 papers
Data mining · 100%
Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › plant biology
plant species identification
0.322013
Pl@ntNet mobile app · ACM Multimedia 2013
Visual-based plant species identification from crowdsourced data · ACM Multimedia 2011
Data mining › crowdsourcing
crowdsourced data
0.012013
Pl@ntNet mobile app · ACM Multimedia 2013
Multimedia analysis and retrieval
image retrieval
0.012013
Pl@ntNet mobile app · ACM Multimedia 2013
Data mining
crowdsourcing
0.012011
Visual-based plant species identification from crowdsourced data · ACM Multimedia 2011

Methods — techniques the papers use, named apart from their topics

content-based image retrieval · 0.7collaborative workflow · 0.5
YearPublicationVenuePosition
2016 A look inside the Pl@ntNet experience - The good, the bias and the hope
Alexis Joly, Pierre Bonnet, Hervé Goëau, Julien Barbe, Souheil Selmi, Julien Champ, Samuel Dufour-Kowalski, Antoine Affouard, Jennifer Carré, Jean-François Molino, Nozha Boujemaa, Daniel Barthélémy
Multim. Syst.10
2016 Plant identification: man vs. machine - LifeCLEF 2014 plant identification challenge
Pierre Bonnet, Alexis Joly, Hervé Goëau, Julien Champ, Christel Vignau, Jean-François Molino, Daniel Barthélémy, Nozha Boujemaa
Multim. Tools Appl.6
2013 Pl@ntNet mobile app
abstract
[email protected] is an image sharing and retrieval application for the identification of plants, available on iPhone and iPad devices. Contrary to previous content-based identification applications it can work with several parts of the plant including flowers, leaves, fruits and bark. It also allows integrating user's observations in the database thanks to a collaborative workflow involving the members of a social network specialized on plants. Data collected so far makes it one of the largest mobile plant identification tool.
Hervé Goëau, Pierre Bonnet, Alexis Joly, Vera Bakic, Julien Barbe, Itheri Yahiaoui, Souheil Selmi, Jennifer Carré, Daniel Barthélémy, Nozha Boujemaa, Jean-François Molino, Grégoire Duché, Aurélien Péronnet
ACM Multimedia11
2011 Visual-based plant species identification from crowdsourced data
abstract
This demo presents a crowdsourcing web application dedicated to the access of botanical knowledge through automated identification of plant species by visual content. Inspired by citizen sciences, our aim is to speed up the collection and integration of raw botanical observation data, while providing to potential users an easy and efficient access to this botanical knowledge. The result presented during the demo is an enjoying application where anyone can play to shoot fresh cut leaves and observe the relevance of species suggested in spite of various visual difficult queries.
Hervé Goëau, Alexis Joly, Souheil Selmi, Pierre Bonnet, Elise Mouysset, Laurent Joyeux, Jean-François Molino, Philippe Birnbaum, Daniel Barthélémy, Nozha Boujemaa
ACM Multimedia7