LifeCLEF Bird Identification Task 2015

International audienceThe LifeCLEF bird identification task provides a testbed for a system-oriented evaluation of 999 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 closer to the conditions of a real-world application than previous, similar initiatives. This overview presents the resources and the assessments of the task, summarizes the retrieval approaches employed by the participating groups, and provides an analysis of the main evaluation results

A marfclef approach to lifeclef 2015 tasks

Abstract. We make the first use of MARF of fast signal-processing and related techniques for LifeCLEF 2015 identification tasks. We build an application based on a pattern recognition pipeline implemented in an open-source Modular A* Recognition Framework (MARF). MARF is also the name of the team in this submission. For that purpose to test and select among available algorithm a set of suitable algorithms. This is the first implementation of the application we call MARFCLEFApp tested on a very small subset of algorithms available. The approach covers Bird-, Plant-, and FishCLEF tasks. It was expected the bird task would be the best for the presented approach given MARF's original intent for audio recognition. However, lack of enough run-time it turned out to be the worst one and is under the investigation. Processing FishCLEF however yield the best of the three tasks, which was expected to be the worst. Team MARF's results for FishCLEF were the 2nd team after with the Run 1 being the best of the three