Automatic separation of objects in images containing multiple plankton organisms
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Automatic separation of objects in images containing multiple plankton organisms
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Thunderstorm nowcast based on radar data (for agrometeorology)
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Integration of DeepaaS API and litter assessment software
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Train your own image classifier, object detection, or segmentation model with your custom dataset using the YOLOv8 model.
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Object detection using FasterRCNN model(s) (fasterrcnn_pytorch_api)
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WIP Identification of marine species from EMSO Azores deep-sea obervatory
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We suggest a 2D image segmentation model based on UNET algorithm to segment images with blossoming apple tree
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Semantic segmentation with Unet Deep Learning model applied to segment Cercospora Leaf Spot.
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A toy application for demo and testing purposes. We just implement dummy inference, ie. we return the same inputs we are fed.
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A module to apply artistic style transfer using pytorch.
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Classify audio files among bird species from the Xenocanto dataset.
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A trained Region Convolutional Neural Network (Faster RCNN) for object detection and classification.
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2D semantic segmentation trained on the Vaihingen dataset
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Train your own audio classifier with your custom dataset. It comes also pretrained on the 527 AudioSet classes.
Know more »»Train a speech classifier to classify audio files between different keywords.
Know more »»Deep learning for proactive network monitoring and security protection.
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Classify conus images among 70 species.
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Train your own image classifier with your custom dataset. It comes also pretrained on the 1K ImageNet classes.
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Classify chest x-ray images in patological and non patological with this x-ray classifier.
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Classify phytoplankton images among 60 classes.
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Classify plant images among 10K species from the iNaturalist dataset.
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Upscale (superresolve) low resolution bands to high resolution in multispectral satellite imagery.
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Classify seeds images among 700K species.
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Identify a dogs breed on the image (133 known breeds)
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A Tensorflow model to classify Retinopathy.
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