diff --git a/content/models/deep-oc-conus-classification-theano.md b/content/models/deep-oc-conus-classification-theano.md index d9522799bf73146a8903a63ad0462cf6f8fa96a4..1b2528f04c7db65bad5e6f6820c9a0edabba7b6d 100644 --- a/content/models/deep-oc-conus-classification-theano.md +++ b/content/models/deep-oc-conus-classification-theano.md @@ -10,7 +10,7 @@ License: Apache License 2.0 Summary: A trained ResNet50 on Theano to classify conus marine snails. --- -[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-conus-classification-theano/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-conus-classification/job/master) +[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-conus-classification/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-conus-classification/job/master) This service is deprecated. Please refer to the [newer Tensorflow version](./deep-oc-conus-classification.html) diff --git a/content/models/deep-oc-conus-classification.md b/content/models/deep-oc-conus-classification.md index d5b722fb65e456edcb7e310b116c0bc194644d48..63bb0bab709b2af48326c420ead5d6250a2e0697 100644 --- a/content/models/deep-oc-conus-classification.md +++ b/content/models/deep-oc-conus-classification.md @@ -2,7 +2,7 @@ Title: DEEP OC Conus Classification Date: 2019-01-01 Category: services, library/tensorflow, library/lasagne, docker -GitHub: https://github.com/deephdc/DEEP-OC-image-classification-tf +GitHub: https://github.com/deephdc/DEEP-OC-conus-classification-tf DockerHub: deephdc/deep-oc-conus-classification-tf Training_files: https://cephrgw01.ifca.es:8080/swift/v1/conus-tf/ License: Apache License 2.0 @@ -15,7 +15,7 @@ Citizen science has become a powerful force for scientific inquiry, providing re data points while connecting non scientists to the real process of science. This citizen-researcher relationship creates a very interesting synergy, allowing for the creation, execution, and analysis of research projects. With this in mind, a Convolutional Neural Network using ResNet50 has been trained to identify conus -marine snails at species level [1] in collaboration with the Museo de Ciencias Naturales in Madrid [2]. +marine snails at species level [1] in collaboration with the Natural Science Museum in Madrid [2]. The taxonomy of these snails has changed significantly several times during recent years and the introduction of Deep Learning techniques allowing to classify them is a very valuable tool for the experts. @@ -33,6 +33,6 @@ This service is based in the [Image Classification with Tensorflow](./deep-oc-im [1]: Puillandre, N.; Duda, T.F.; Meyer, C.; Olivera, B.M.; Bouchet, P. (2014). "One, four or 100 genera? A new classification of the cone snails". Journal of Molluscan Studies. 81 (1): 1–23. doi:10.1093/mollus/eyu055. PMC 4541476. PMID 26300576. -[2]: http://www.mncn.csic.es/ +[2]: Natural Science Museum of Madrid: http://www.mncn.csic.es/ [3]: Chollet, François. [Xception: Deep learning with depthwise separable convolutions](https://arxiv.org/abs/1610.02357) arXiv preprint (2017): 1610-02357. diff --git a/content/models/deep-oc-phytoplankton-classification-theano.md b/content/models/deep-oc-phytoplankton-classification-theano.md index 4c7beda0a3adef014e7e321c8ae35d27d28fe2c2..22f8831324fb2191023b700ebc73d33df24f192d 100644 --- a/content/models/deep-oc-phytoplankton-classification-theano.md +++ b/content/models/deep-oc-phytoplankton-classification-theano.md @@ -9,7 +9,7 @@ License: Apache License 2.0 Summary: A trained ResNet50 on Theano to classify phytoplankton species. --- -[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-phytoplankton-classification-theano/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-phytoplankton-classification/job/master) +[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-phytoplankton-classification/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-phytoplankton-classification/job/master) This service is deprecated. Please refer to the [newer Tensorflow version](./deep-oc-phytoplankton-classification.html) diff --git a/content/models/deep-oc-phytoplankton-classification.md b/content/models/deep-oc-phytoplankton-classification.md index 60f416d4f59fd6a2a6ccd214e43d19efcf5ab4a3..bad1f58b286ebb0a8e9e6b7f973b6e968f4ee380 100644 --- a/content/models/deep-oc-phytoplankton-classification.md +++ b/content/models/deep-oc-phytoplankton-classification.md @@ -2,14 +2,14 @@ Title: DEEP OC Phytoplankton Date: 2019-01-01 Category: services, library/tensorflow, library/lasagne, docker -GitHub: https://github.com/deephdc/DEEP-OC-image-classification-tf +GitHub: https://github.com/deephdc/DEEP-OC-phytoplankton-classification-tf DockerHub: deephdc/deep-oc-phytoplankton-classification-tf Training_files: https://cephrgw01.ifca.es:8080/swift/v1/phytoplankton-tf/ License: Apache License 2.0 Summary: A trained Xception net on Tensorflow/Keras to classify phytoplankton. --- -[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-phytoplankton-classification-theano/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-phytoplankton-classification/job/master) +[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/DEEP-OC-phytoplankton-classification-tf/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/DEEP-OC-phytoplankton-classification-tf/job/master) The deep learning revolution has brought significant advances in a number of fields [1], primarily linked to image and speech recognition. The diff --git a/content/models/deep-oc-retinopathy.md b/content/models/deep-oc-retinopathy.md index b9008916d365bf92332c7da59a5fd158592cf358..0bed338e2ade6de897d4a6a44c4b7e951c8cd897 100644 --- a/content/models/deep-oc-retinopathy.md +++ b/content/models/deep-oc-retinopathy.md @@ -9,6 +9,8 @@ License: Apache License 2.0 Summary: --- +[![Build Status](https://jenkins.indigo-datacloud.eu:8080/buildStatus/icon?job=Pipeline-as-code/DEEP-OC-org/retinopathy_test/master)](https://jenkins.indigo-datacloud.eu:8080/job/Pipeline-as-code/job/DEEP-OC-org/job/retinopathy_test/job/master) + This use case is concerned with the classification of biomedical images (of the retina) into five disease categories or stages (from healthy to severe) using a deep learning approach. This is a TensorFlow example implementation. The network is a standard residual network model with 50 layers (ResNet50). The model used in this use case was made available by Niklas Köhler: https://gitlab.com/niklaskoehler/retinopathy_model Retinopathy is a fast-growing cause of blindness worldwide, over 400 million people at risk from diabetic retinopathy alone [Yau2012]. The disease can be successfully treated if it is detected early. Colour fundus retinal photography uses a fundus camera (a specialized low power microscope with an attached camera) to record color images of the condition of the interior surface of the eye, in order to document the presence of disorders and monitor their change over time. Specialized medical experts interpret such images and are able to detect the presence and stage of retinal eye disease such as diabetic retinopathy. However, due to a lack of suitably qualified medical specialists in many parts of the world a comprehensive detection and treatment of the disease is difficult. This use case focuses on a deep learning approach to automated classification of retinopathy based on color fundus retinal photography images [Eul2017]. diff --git a/content/models/deep-oc-seed-classification.md b/content/models/deep-oc-seed-classification.md index 80e9ef1a98649fa90c33162b9d3cafc5286d4ca3..715134d05b5bdf6958d0a07b06ff586fbaf7792f 100644 --- a/content/models/deep-oc-seed-classification.md +++ b/content/models/deep-oc-seed-classification.md @@ -2,7 +2,7 @@ Title: DEEP OC Seeds Classification Date: 2019-01-01 Category: services, library/tensorflow, library/lasagne, docker -GitHub: https://github.com/deephdc/DEEP-OC-image-classification-tf +GitHub: https://github.com/deephdc/DEEP-OC-seeds-classification-tf DockerHub: deephdc/deep-oc-seeds-classification-tf Training_files: https://cephrgw01.ifca.es:8080/swift/v1/seeds-tf/ License: Apache License 2.0