B.3: YOLO: image detection architectures: Difference between revisions
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• '''Short Description''': | • '''Short Description''': | ||
YOLOv5 is a family of compound-scaled object detection models trained on the COCO dataset, and includes simple functionality for Test Time Augmentation (TTA), model ensembling, hyperparameter evolution, and export to ONNX, CoreML and TFLite. | |||
• '''Reference, URL''': https://pytorch.org/hub/datvuthanh_hybridnets/ | |||
• '''Reference, URL''': | |||
• '''Relevant Domain/Industry''': WEEE & Battery | • '''Relevant Domain/Industry''': WEEE & Battery | ||
• '''Application in relevant Projects/Initiatives''': | • '''Application in relevant Projects/Initiatives''': N.A. | ||
• '''Type''': | • '''Type''': ML Model | ||
• '''AI Breadth''': | • '''AI Breadth''': DL, computer vision | ||
• '''Learning Ability''': | • '''Learning Ability''': Supervised learning | ||
• '''Related technologies''': | • '''Related technologies''': Pytorch | ||
• '''License Information''': | • '''License Information''': MIT license (MIT) | ||
• '''Related to circularity and sustainability''': | • '''Related to circularity and sustainability''': No | ||
• '''Audience''': Manufacturer | • '''Audience''': Manufacturer | ||
Revision as of 14:21, 26 April 2023
• Short Description: YOLOv5 is a family of compound-scaled object detection models trained on the COCO dataset, and includes simple functionality for Test Time Augmentation (TTA), model ensembling, hyperparameter evolution, and export to ONNX, CoreML and TFLite.
• Reference, URL: https://pytorch.org/hub/datvuthanh_hybridnets/
• Relevant Domain/Industry: WEEE & Battery
• Application in relevant Projects/Initiatives: N.A.
• Type: ML Model
• AI Breadth: DL, computer vision
• Learning Ability: Supervised learning
• Related technologies: Pytorch
• License Information: MIT license (MIT)
• Related to circularity and sustainability: No
• Audience: Manufacturer
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