Hi (again),
> The RNN model can then be shipped into a QGIS Plugin with a convenient > interface such that one could accomplish the following tasks: > > - Select the input data; > > > - Adjust some model hyperparameters (if desirable); > > > - Train the RNN; > > > - Export the generated model for persistence; > > > - Use the model to produce a LCLU map for the specified targets. > > The idea is to start a new Plugin that use not only RNN models, but, in > the future, incorporate many other novel approaches to perform accurate LCLU > maps, like semantic segmentation using U-Nets and a combination of the two > approaches. > Not everyone probably wants (or has the resources) to train the data. Why not, for example, have a model zoo platform where users can share their models for particular defined classifications? or will the training always be lightweight and instant? Cheers On Fri, Mar 23, 2018 at 2:52 PM, Evandro Carrijo <[email protected]> wrote: > Hello there! > > I'm a Computer Science Master's Degree student whose research if focused > on Deep Learning algorithms applied to Remote Sensing. Currently working at > the Laboratory of Image Processing and Geoprocessing > <https://github.com/lapig-ufg> settled at Federal University of Goiás - > Brazil. I'm also member of the High Performance Computing group of the same > university (more information here > <http://dgp.cnpq.br/dgp/espelhogrupo/7985061476854055>). > > Below I present an idea to explain how I can contribute to OSGeo/QGIS > community and I'm seeking for mentors interested in assist my development. > Please, feel free to argue me any matter about the project idea. > > I would also appreciate a lot if you guys indicate a potential interested > mentor to my project idea. > > Hope there's some Interested ones out there! > > Idea > > The increasing number of sensors orbiting the earth is systematically > producing larger volumes of data, with better spatiotemporal resolutions. > To deal with that, better accurate machine learning approaches, such as > Deep Learning (DL), are needed to transform raw data into applicable > Information. Several DL architectures (e.g. CNN, semantic segmentation) > rely only at spatial dimension to perform, for example, land-cover/land-use > (LCLU) maps, disregarding the temporal dependencies between pixels > observations over the time. Also, high-res remote sensing data (e.g. > Planet, Sentinel) may provide more consistent time-series, that can be use > in the identification of important LCLU classes, like crop, pastureland and > grasslands. > > This potential can be explored using Recurrent Neural Networks (RNN), a > specific family of DL approaches which can take into account time > dimension. A promising project idea would be implement a RNN approach (e.g. > LSTM) to classify, for example, a Sentinel time-series, that will organize > and preprocess the input data set (e.g. labeled time-series), calibrate and > evaluate a RNN model, and finally classify an entire region (i.e. 2 or 3 > scenes) to produce a map for one or more LCLU class. It will be great > evaluate the accuracy and the spatial consistent of a map produced with a > RNN approach. > > The RNN model can then be shipped into a QGIS Plugin with a convenient > interface such that one could accomplish the following tasks: > > > - Select the input data; > - Adjust some model hyperparameters (if desirable); > - Train the RNN; > - Export the generated model for persistence; > - Use the model to produce a LCLU map for the specified targets. > > The idea is to start a new Plugin that use not only RNN models, but, in > the future, incorporate many other novel approaches to perform accurate LCLU > maps, like semantic segmentation using U-Nets and a combination of the two > approaches. > > A simple example on classifying LCLU with two classes (pastureland and > non-pastureland): > > [image: itapirapua] > <https://user-images.githubusercontent.com/37085598/37687055-cc5236a8-2c78-11e8-8892-d113df44e235.jpg> > *Target region (input)* > > [image: itapirapua_ref] > <https://user-images.githubusercontent.com/37085598/37732806-ec792782-2d24-11e8-8ad9-18867768e998.jpg> > *Generated LCLU map (output)* > Best, > > Evandro Carrijo Taquary > Federal University of Goiás > > _______________________________________________ > QGIS-Developer mailing list > [email protected] > List info: https://lists.osgeo.org/mailman/listinfo/qgis-developer > Unsubscribe: https://lists.osgeo.org/mailman/listinfo/qgis-developer > -- *Akbar Gumbira * *www.akbargumbira.com <http://www.akbargumbira.com>*
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