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Showing 5 open source projects for "https"
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Phenalysis
Analyze agronomic plant research plots in aerial orthomosaic images.
...Please cite the following reference in your work if you use Phenalysis: Khan Z and Miklavcic SJ (2019) An Automatic Field Plot Extraction Method From Aerial Orthomosaic Images. Front. Plant Sci. 10:683. doi: https://doi.org/10.3389/fpls.2019.00683 This tool is being developed through the sponsorship of the Australian Research Council's Industrial Transformation Research Hub on Wheat in a Hot and Dry Climate. https://www.wheathub.com.au/ -
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Mass-based dissimilarity
A data dependent dissimilarity measure based on mass estimation.
...KDD 2016 http://dx.doi.org/10.1145/2939672.2939779 The source code, presentation slide and poster are attached under "Files". The presentation video in KDD 2016 is published on https://youtu.be/eotD_-SuEoo . Since this software is licensed under the Gnu General Public license GPLv3, any derivative work must be licensed under the GPL as well. This software is free only for non-commercial use. For commercial projects, it is possible to obtain a commercial license through the Commercial Services of Federation University Australia. ... -
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SPIW - Scanning Probe Image Wizard
Scanning Probe Image Wizard - MATLAB Toolbox
...For information on SPIW's performance see our publication ( http://dx.doi.org/10.1063/1.4827076 ) in the Review of Scientific Instruments. A related open-source project SPIEPy (https://pypi.python.org/pypi/SPIEPy/) is developing a python library to for automated SPM imaged enhancement. SPIEPy brings many SPIW algorithms to the Python user. -
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AEO-Light 1.1
Version 1.1 is no longer supported.
Version 1.1 is no longer supported. Please see the new version at https://usc-imi.github.io/aeo-light/ Description for 1.1 continues below: AEO-Light 1.1 is an open-source software application that takes a digital scan of motion picture film with optical sound tracks and directly reproduces the audio, producing as a result a synchronized sound film file. Funded by a grant from the National Endowment for the Humanities and by the University of South Carolina. -
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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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