Train your own image classifier, object detection, or segmentation model with your custom dataset using the YOLOv8 model.
Object detection using FasterRCNN model(s) (fasterrcnn_pytorch_api)
We suggest a 2D image segmentation model based on UNET algorithm to segment images with blossoming apple tree
A module to apply artistic style transfer using pytorch.
Classify audio files among bird species from the Xenocanto dataset.
tf_cnn_benchmarks accessed via DEEPaaS API
A trained Region Convolutional Neural Network (Faster RCNN) for object detection and classification.
2D semantic segmentation trained on the Vaihingen dataset
Train your own audio classifier with your custom dataset. It comes also pretrained on the 527 AudioSet classes.
Train a speech classifier to classify audio files between different keywords.
Deep learning for proactive network monitoring and security protection.
Classify conus images among 70 species.
Train your own image classifier with your custom dataset. It comes also pretrained on the 1K ImageNet classes.
Classify chest x-ray images in patological and non patological with this x-ray classifier.
Classify phytoplankton images among 60 classes.
Classify plant images among 10K species from the iNaturalist dataset.
Upscale (superresolve) low resolution bands to high resolution in multispectral satellite imagery.
Classify seeds images among 700K species.
Identify a dogs breed on the image (133 known breeds)
A Tensorflow model to classify Retinopathy.