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​​Perceiver IO: a scalable, fully-attentional model that works on any modality

#HuggingFace added neural network which is capable of working on all kinds of modailities: text, images, audio, video, coordinates, etc to the transformers library.

Blog: https://huggingface.co/blog/perceiver

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@data_enthusiasts
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PASS: Pictures without humAns for Self-Supervised Pretraining

PASS is a large-scale image dataset that does not include any humans, human parts, or other personally identifiable information

Github
https://github.com/yukimasano/PASS

Paper
https://arxiv.org/abs/2109.13228v1

Dataset
https://paperswithcode.com/dataset/pass

Documentation
https://www.robots.ox.ac.uk/~vgg/research/pass/

Team
@data_enthusiasts
@OpenArchiveBooks
80+ Jupyter Notebook tutorials on image classification, object detection and image segmentation in various domains

πŸ“Œ Agriculture and Food
πŸ“Œ Medical and Healthcare
πŸ“Œ Satellite
πŸ“Œ Security and Surveillance
πŸ“Œ ADAS and Self Driving Cars
πŸ“Œ Retail and E-Commerce
πŸ“Œ Wildlife


Classification library
https://github.com/Tessellate-Imaging/monk_v1

Notebooks - https://github.com/Tessellate-Imaging/monk_v1/tree/master/study_roadmaps/4_image_classification_zoo

Detection and Segmentation Library
https://github.com/Tessellate-Imaging/

Monk_Object_Detection
Notebooks: https://github.com/Tessellate-Imaging/Monk_Object_Detection/tree/master/application_model_zoo

Team
@data_enthusiasts
@OpenArchiveBooks