IEEE Geospatial Data Fusion Contest
The Contest, which helps connecting students and researchers around the world, evaluates existing methodologies at the research or operational level to solve remote sensing problems using data from various sensors.
Recently, the IEEE Geoscience and Remote Sensing Society announced plans for its 2013 Data Fusion Contest. The Contest, which helps connecting students and researchers around the world, evaluates existing methodologies at the research or operational level to solve remote sensing problems using data from various sensors.
The Contest is open not only to IEEE members, but to everyone, and consists of two parallel competitions: Best Paper Award and Best Classification Award. The winning teams will receive an iPad, an IEEE Certificate of Appreciation, and a free open access publication in an IEEE GRSS Journal. Final results will be announced at the 2013 IEEE International Geoscience and Remote Sensing Symposium in Melbourne, Australia, in July 2013.
Contest details are available
This year, the Contest involves two datasets - a hyperspectral image and a LiDAR derived Digital Surface Model (DSM), both at the same spatial resolution (2.5m). The hyperspectral imagery has 144 spectral bands in the 380 nm to 1050 nm region. The dataset was acquired over the University of Houston campus and the neighboring urban area.
The Contest consists of two parallel competitions. Users are welcome to participate in one or both of them.
1. Best Paper Award, with the objective of promoting novel synergetic use of hyperspectral and LiDAR data. The deliverable will be a 4-page IEEE-style manuscript that addresses the problem, methodology, results and discussion. We encourage the participants to consider various open problems in the realm of multi-sensor data fusion and to use the dataset provided to demonstrate novel and effective approaches to addressing these problems.
2. Best Classification Award, to promote innovation in classification algorithms, and to provide objective and fair performance comparisons among state-of-the-art algorithms. For this task, users will be provided with ground truth to train and gauge the efficacy of their algorithms. Participants will use the ground truth provided to them, along with the multi-sensor dataset, and submit their classification maps and a brief description of the algorithm.
- Best Classification Award - Results to be submitted between February 16, 2013 and May 1, 2013.
- Best Paper Award - Manuscripts to be submitted by May 31, 2013
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