Hervé Goëau

• PhD
• French Agricultural Research Centre for International Development

Deep learning models for plant species identification rely on large annotated datasets. The Pl@ntNet system enables global data collection by allowing users to upload and annotate plant observations, leading to noisy labels due to diverse user skills. Achieving consensus is crucial for training, but the vast scale of collected data (number of obser...

Four of the twenty five diversity hotspots cover Southeast Asia: Sundaland, Philippines, Indo-Burma and Wallacea. All these hotspots gather a large number of endemic species and ecosystems, accounting for 20% of the world's plant, animal and marine species. A better knowledge of this diversity and distribution is thus essential to enable the implem...

Plant morphological traits, their observable characteristics, are fundamental to understand the role played by each species within their ecosystem. However, compiling trait information for even a moderate number of species is a demanding task that may take experts years to accomplish. At the same time, massive amounts of information about species d...

Traditionally, plant pathologists have emphasized controlling crop pathogens, neglecting the importance of conserving their diversity in natural ecosystems. Native plant pathogens thriving in natural environments significantly contribute to ecosystem structure, stability, nutrient cycling, and productivity. The coevolution of wild crop progenitors...

Deep learning models for plant species identification rely on large annotated datasets. The PlantNet system enables global data collection by allowing users to upload and annotate plant observations, leading to noisy labels due to diverse user skills. Achieving consensus is crucial for training, but the vast scale of collected data makes traditiona...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, species identification and inventory is a difficult and costly task, requiring large-scale automated approaches. The LifeCLEF lab has been...

The cultivation of seed mixtures for local pastures is a traditional mixed cropping technique of cereals and legumes for producing, at a low production cost, a balanced animal feed in energy and protein in livestock systems. By considerably improving the autonomy and safety of agricultural systems, as well as reducing their impact on the environmen...

Human activities have a growing impact on global biodiversity. While our understanding of biodiversity worldwide is not yet comprehensive, it is crucial to explore effective means of characterizing it in order to mitigate these impacts. The advancements in data storage, exchange capabilities, and the increasing availability of extensive taxonomic,...

Biodiversity monitoring through AI approaches is essential, as it enables the efficient analysis of vast amounts of data, providing comprehensive insights into species distribution and ecosystem health and aiding in informed conservation decisions. Species identification based on images and sounds, in particular, is invaluable for facilitating biod...

The BirdCLEF 2023 challenge focused on bird species classification in a dataset of Kenyan soundscape recordings. Kenya is home to over 1,000 species of birds, covering a wide range of ecosystems, from the savannahs of the Maasai Mara to the Kakamega rainforest, and even alpine regions on Kilimanjaro and Mount Kenya. Tracking this vast number of spe...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming livi...

We present a new application to recognize 218 species of cultivated crops on geo-tagged photos, ‘Pl@ntNet Crops’. The application and underlying algorithms are developed using more than 750k photos voluntarily collected by Pl@ntNet users. The app is then enriched by data and photos coming from the European Union’s (EU) Land Use and Coverage Area fr...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming livi...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming liv...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants, animals and fungi is hindering the aggregation of new data and knowledge. Identifying and naming livi...

A better knowledge of tree vegetative growth phenology and its relationship to environmental variables is crucial to understanding forest growth dynamics and how climate change may affect it. Less studied than reproductive structures, vegetative growth phenology focuses primarily on the analysis of growing shoots, from buds to leaf fall. In tempera...

Machine learning (ML) can accelerate the extraction of phenological data from herbarium specimens; however, no studies have assessed whether ML-derived phenological data can be used reliably to evaluate ecological patterns. In this study, 709 herbarium specimens representing a widespread annual herb, Streptanthus tortuosus, were scored both manuall...

Pl@ntnet is a citizen observatory that relies on artificial intelligence (AI) technologies to help people identify plants with their smartphones (Joly 2014). Over the past few years, Pl@ntNet has become one of the largest plant biodiversity observatories in the world with several million contributors (Bonnet 2020b). Based on user demands, a set of...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals is hindering the aggregation of new data and knowledge. Identifying and naming living plan...

Automated plant identification has recently improved significantly due to advances in deep learning and the availability of large amounts of field photos. As an illustration, the classification accuracy of 10K species measured in the LifeCLEF challenge (Goëau et al. 2018) reached 90%, very close to that of human experts. However, the profusion of f...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants and animals is hindering the aggregation of new data and knowledge. Identifying and naming living pla...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...

Plant diseases have a significant impact on global food security and the world's agricultural economy. Their early detection and classification increase the chances of setting up effective control measures, which is why the search for automatic systems that allow this is of major interest to our society. Several recent studies have reported promisi...

Pl@ntNet is a scientific and citizen platform based on artificial intelligence techniques to help participants more easily identify plants with their smartphones. The identification of plant species is indeed an important step for many scientific, educational and land management activities (for natural or cultivated spaces). This step, which is int...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...

Passive acoustic monitoring is a cornerstone of the assessment of ecosystem health and the improvement of automated assessment systems has the potential to have a transformative impact on global biodiversity monitoring, at a scale and level of detail that is impossible with manual annotation or other more traditional methods. The BirdCLEF challenge...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However , the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and nami...

Premise: Weed removal in agriculture is typically achieved using herbicides. The use of autonomous robots to reduce weeds is a promising alternative solution, although their implementation requires the precise detection and identification of crops and weeds to allow an efficient action. Methods: We trained and evaluated an instance segmentation...

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens-preserved plant material curated in natural history collections-but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as...

Premise: Herbarium specimens represent an outstanding source of material with which to study plant phenological changes in response to climate change. The fine-scale phenological annotation of such specimens is nevertheless highly time consuming and requires substantial human investment and expertise, which are difficult to rapidly mobilize. Meth...

Building accurate knowledge of the identity, the geographic distribution and the evolution of species is essential for the sustainable development of humanity, as well as for biodiversity conservation. However, the difficulty of identifying plants and animals in the field is hindering the aggregation of new data and knowledge. Identifying and namin...

Con base en las recientes aplicaciones exitosas de técnicas de Aprendizaje Profundo en la clasificación, detección y segmentación de plantas, proponemos un enfoque de segmentación de instancias utilizando un modelo Mask R-CNN para la detección de malezas y cultivos en tierras de cultivo. Evaluamos el rendimiento de nuestro modelo con la métrica de...

The control of plant diseases is a major challenge to ensure global food security and sustainable agriculture. Several recent studies have proposed to improve existing procedures for early detection of plant diseases through modern automatic image recognition systems based on deep learning. In this article, we study these methods in detail, especia...

Pl@ntNet is a scientific and citizen platform based on artificial intelligence techniques to help participants more easily identify plants with their smartphones. The identification of plant species is indeed an important step for many scientific, educational and land management activities (for natural or cultivated spaces). This step, which is int...

La diversité des habitats du Parc national des Cévennes héberge une flore riche, composée de plus de 2400 espèces (angiospermes, gymnospermes et fougères). Une bonne connaissance de cette flore est essentielle pour le développement de stratégies de gestion adaptées. Les ressources humaines étant cependant limitées, l’appui des résidents et visiteur...

Identifying and naming living plants or animals is usually impossible for the general public and often a difficult task for professionals and naturalists. Bridging this gap is a key challenge towards enabling effective biodiversity information retrieval systems. This taxonomic gap was actually already identified as one of the main ecological challe...

Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. Unfortunately, such basic information is often only partially available for professional stakeholders, teachers, scientists and citizens, and o...

Millions of herbarium records provide an invaluable legacy and knowledge of the spatial and temporal distributions of plants over centuries across all continents (Soltis et al. 2018). Due to recent efforts to digitize and to make publicly accessible most major natural collections, investigations of ecological and evolutionary patterns at unpreceden...

Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. However, the burden of the routine identification of plants and animals in the field is strongly penalizing the aggregation of new data and kno...

Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity, as well as for biodiversity conservation. However, the burden of the routine identification of plants and animals in the field is strongly penalizing the aggregation of new data and kno...

Premise of the Study Phenological annotation models computed on large‐scale herbarium data sets were developed and tested in this study. Methods Herbarium specimens represent a significant resource with which to study plant phenology. Nevertheless, phenological annotation of herbarium specimens is time‐consuming, requires substantial human investm...

AcknowledgementsThe organization of the PlantCLEF task is supported by the French project Floris’Tic (Tela Botanica, INRIA, CIRAD, INRA, IRD) funded in the context of the national investment program PIA. The organization of the BirdCLEF task is supported by the Xeno-Canto foundation for nature sounds as well as the French CNRS project SABIOD.ORG an...

The estimated number of flowering plant species on Earth is around 400,000. In order to classify all known species via automated image-based approaches, current datasets of plant images will have to become considerably larger. To achieve this, some authors have explored the possibility of using herbarium sheet images. As the plant datasets grow and...

Automated identification of plants and animals have improved considerably in the last few years, in particular thanks to the recent advances in deep learning. The next big question is how far such automated systems are from the human expertise. Indeed, even the best experts are sometimes confused and/or disagree between each others when validating...

Automated identification of plants and animals has improved considerably in the last few years, in particular thanks to the recent advances in deep learning. In order to evaluate the performance of automated plant identification technologies in a sustainable and repeatable way, a dedicated system-oriented benchmark was setup in 2011 in the context...

Pl@ntNet is an international initiative which was the first one attempting to combine the force of citizens networks with automated identification tools based on machine learning technologies (Joly et al. 2014). Launched in 2009 by a consortium involving research institutes in computer sciences, ecology and agriculture, it was the starting point of...

Background Hundreds of herbarium collections have accumulated a valuable heritage and knowledge of plants over several centuries. Recent initiatives started ambitious preservation plans to digitize this information and make it available to botanists and the general public through web portals. However, thousands of sheets are still unidentified at t...

Pl@ntNet is a world-scale participatory platform and information system dedicated to the monitoring of plant biodiversity through image-based plant identification. Nowadays, the mobile front-end of Pl@ntNet has been downloaded by more than 4 millions users in about 170 countries and an active community of contributors produce and revise new observa...

Automated multimedia identification tools are an emerging solution towards building accurate knowledge of the identity, the geographic distribution and the evolution of living plants and animals. Large and structured communities of nature observers as well as big monitoring equipment have actually started to produce outstanding collections of multi...

Hundreds of herbarium collections have accumulated a valuable heritage and knowledge of plants over several centuries (Page et al. 2015). Recent initiatives, such as iDigBio (https://www.idigbio.org), aggregate data from and images of vouchered herbarium sheets (and other biocollections) and make this information available to botanists and the gene...

LifeCLEF (www.lifeclef.org) is a worldscale research forum dedicated to the evaluation of multimedia-oriented identification systems. Its principle is to measure and boost the performance of the state-of-the-art by sharing large-scale experimental data covering thousands of species. Methods Each year, hundreds of research groups register to the pro...

Large scale biodiversity monitoring is essential for sustainable development (earth stewardship). With the recent advances in computer vision, we see the emergence of more and more effective identification tools allowing to set-up large-scale data collection platforms such as the popular Pl@ntNet initiative that allow to reuse interaction data. Alt...

Using multimedia identification tools is considered as one of the most promising solutions to help bridge the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g., iSpot, Xeno-canto, Tela Botanica, etc.) as well as big...

The LifeCLEF bird identification challenge provides a large-scale testbed for the system-oriented evaluation of bird species identification based on audio recordings. One of its main strength is that the data used for the evaluation is collected through Xeno-Canto, the largest network of bird sound recordists in the world. This makes the task close...

Pl@ntNet is an innovative participatory sensing platform relying on image-based plants identification as a mean to enlist non-expert contributors and facilitate the production of botanical observation data. One year after the public launch of the mobile application, we carry out a self-critical evaluation of the experience with regard to the requir...

Pl@ntNet est un réseau humain s'appuyant sur une infrastructure informatique, permettant l'identification, l'agrégation et le partage d'observations botaniques à très grande échelle. Cette initiative mobilise différentes institutions de recherche dans divers champs scientifiques (informatique, agronomie, écologie) et de larges réseaux associatifs d...

Using multimedia identification tools is considered as one of the most promising solutions to help bridging the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g. eBird, Xeno-canto, Tela Botanica, etc.) as well as big...

The LifeCLEF plant identification challenge aims at evaluating plant identification methods and systems at a very large scale, close to the conditions of a real-world biodiversity monitoring scenario. The 2015 evaluation was actually conducted on a set of more than 100K images illustrating 1000 plant species living in West Europe. The main original...

This paper reports a large-scale experiment aimed at evaluating how state-of-art computer vision systems perform in identifying plants compared to human expertise. A subset of the evaluation dataset used within LifeCLEF 2014 plant identification challenge was therefore shared with volunteers of diverse expertise, ranging from the leading experts of...

Pl@ntNet is an innovative participatory sensing platform relying on image-based plants identification as a mean to enlist non-expert contributors and facilitate the production of botanical observation data. One year after the public launch of the mobile application, we carry out a self-critical evaluation of the experience with regard to the requir...

This paper discusses the results of the LifeCLEF 2014 multimedia identification challenges with regards to the requirements of real-world ecological surveillance systems. In particular, we study the identification performances of the evaluated systems as a function of the ordinariness or rarity of the species in the dataset. This allows us to asses...

Using multimedia identification tools is considered as one of the most promising solutions to help bridging the taxonomic gap and build accurate knowledge of the identity, the geographic distribution and the evolution of living species. Large and structured communities of nature observers (e.g. eBird, Xeno-canto, Tela Botanica, etc.) as well as big...

The LifeCLEF bird identification task provides a testbed for a system-oriented evaluation of 501 bird species identification. The main originality of this data is that it was specifically built through a citizen science initiative conducted by Xeno-Canto, an international social network of amateur and expert ornithologists. This makes the task clos...

Building accurate knowledge of the identity, the geographic distribution and the evolution of living species is essential for a sustainable development of humanity as well as for biodiversity conservation. In this context, using multimedia identification tools is considered as one of the most promising solution to help bridging the taxonomic gap. W...