Warning: Please be aware that these videos are a snapshot, and as such may use an outdated version of the tutorial and/or Galaxy. Below the video you will find links to the tutorials as they appeared at the time of recording.
Image classification in Galaxy with fruit 360 dataset
Below are video tutorials for this GTN material, created for various (past) events.Tutorial Video (January 2022)
| Description: | The classification of fruits and vegetables offers many useful applications such as automated harvesting by robots, building up stocks for supermarkets, effective detection of specific defects, and determining fruit ripeness (Duong et al. 2020, Naranjo-Torres et al. 2020, Iswari et al. 2017). Machine Learning (ML) techniques such as Deep Learning (DL) are commonly used for image classification problems in various domains, including in agriculture (Kamilaris and Prenafeta-Boldú 2018). DL is a technique inspired by how a human brain operates. Due to the increased availability of compute capacity and training data, DL techniques have become very popular in recent years. In this tutorial, we will use Galaxy’s ML toolkit to build a DL model to classify fruit and vegetable images. Our DL model is trained and evaluated on Fruit 360 dataset (Mureşan and Oltean 2018) |
| Length: | 1 hour |
| Captions: | Kaivan Kamali |
| Created: | 19 January 2022 |
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| Supported Servers: | Known Working |
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