Postdoctoral position in the field of Image analysis and adaptation of algorithms for automatic recognition and classification of plankton
In the framework of the studies concerning the impact of the climatic change on the aquatic ecosystems, the long term series analysis in the different geographic provinces is essential. Species or species assemblages of plankton are good indicators of regime shifts and modifications in their community structure or in their population dynamics are used both in studies concerning the response of the ecosystem to environmental forcings, and in predictive modelling of the processes related to these changes. The Laboratoire d’Oceanographie de Villefranche (LOV) is one of the European forerunners of the application of zooplankton imaging techniques at sea and in the laboratory. Several instruments based on these methods were built and are in use. The technology of the Underwater Video Profiler and of the Zooscan was transferred towards the SMEs. Nevertheless, the treatment of the data and their analyses remain a scientific activity that is carried out in LOV.
There is a need for a classification system capable of handling images from a variety of in situ and laboratory imaging systems; providing users with a broad selection of classification algorithms; and classifying images with a high degree of accuracy that is at least comparable to the performance of a human expert.
The importance of such system is :
1) in the reduction of the delays of analyses in the treatment of long time series,
2) the construction of classifiers allowing rapid assessment of the temporal and spatial evolution of the functional groups of plankton, and
3) the creation of networks for experts’ interaction.
In order to fully exploit the imaging instruments, and to automate the treatments, we must reinforce our competences in the treatments of images sensu stricto and develop feature extraction tools and algorithms for recognition and classification of the objects. It is imperative to develop algorithms allowing the identification and analysis of complex natural objects in a noisy environment.
The objective of this project is the development of approaches allowing the implementation of algorithms for image treatment and analysis of descriptive parameters which will be introduced into neural network and numerical analyses for the final classification. At first, these methods will be applied on the long time series of the Mediterranean Sea.
This proposition concerns specialists in the image treatment and analysis software development. The aim is the adaptation of ‘intelligent’ systems for the automated recognition and classification of aquatic organisms. Skills of the candidate are wished in following domains:
application of neural network and classifiers construction;
development of classification algorithms;
development of algorithms for extraction of the descriptive attributes of objects;
development of applications to assess the quality of objects and their morphological structure;
detection of objects in a noisy environment;
image treatment (correction, filtration techniques, arithmetical, logical and geometric treatments);
image analysis (histogram, particles analysis);
image compression and storage
How to proceed :
3- Fill the form and submit before April 30 to the contact person: Dr. Gabriel Gorsky
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