computer_vision_and_pattern_recognition_segmentation_d_image
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computer_vision_and_pattern_recognition [2019/03/05 10:45] – [Ressources] serge | computer_vision_and_pattern_recognition_segmentation_d_image [2020/02/04 16:23] – ↷ Liens modifiés en raison d'un déplacement. serge | ||
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- | ====== Computer Vision and Pattern Recognition ====== | + | ====== Computer Vision and Pattern Recognition |
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- | {{: | + | {{ youtube> |
+ | **Une bonne explication de l' | ||
</ | </ | ||
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- | {{:2019_03: | + | {{ youtube> |
+ | **Les réseaux de convolution (CNN)** | ||
+ | </ | ||
+ | </ | ||
+ | |||
+ | <WRAP group> | ||
+ | <WRAP half column> | ||
+ | {{ media_01:polarlicht_2.jpg? | ||
+ | </ | ||
+ | <WRAP half column> | ||
+ | {{ media_01: | ||
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Wikipedia dit que la **[[https:// | Wikipedia dit que la **[[https:// | ||
- | La **[[https:// | + | La [[https:// |
+ | =====YOLO===== | ||
+ | {{ youtube> | ||
+ | |||
+ | Yolo v3 est utilisé avec: | ||
+ | * **[[yolo_darknet_avec_un_vrai_semaphore|Yolo Darknet avec un vrai sémaphore]]** | ||
+ | =====Définition de Mask R-CNN===== | ||
+ | |||
+ | Les Perceptron, Perceptron multi-couche, | ||
+ | ====R-CNN==== | ||
+ | **R-CNN** = **R**egional **C**onvolutional **N**eural **N**etwork | ||
+ | |||
+ | ====Mask R-CNN==== | ||
+ | |||
+ | * [[https:// | ||
+ | * [[https:// | ||
+ | |||
+ | =====MASK R-CNN vs YOLO vs Deeplab Xception===== | ||
+ | Un peu de zik: {{ youtube> | ||
+ | * [[https:// | ||
+ | * [[https:// | ||
+ | * [[https:// | ||
=====Ressources===== | =====Ressources===== | ||
- | * **[[https://arxiv.org/abs/1703.06870|Mask R-CNN]]** | + | ====ImageNet==== |
- | | + | |
+ | |||
+ | ====COCO Common Object in Context==== | ||
+ | * [[http:// | ||
+ | |||
+ | ====ROI==== | ||
+ | **ROI = Region of interest** | ||
+ | |||
+ | * [[https://en.wikipedia.org/wiki/Region_of_interest|Region of interest]] | ||
+ | **Mask R-CNN** | ||
+ | * [[https:// | ||
+ | |||
+ | **Region of Interest** pooling (also known as RoI pooling ou Roi) is a variant of max pooling, in which output size is fixed and input rectangle is a parameter. | ||
- | [[https:// | + | Pooling is an important component of convolutional neural networks for object detection based on Fast R-CNN architecture. |
- | [[https://www.kaggle.com/pytorch/resnet101|ResNet101]] | + | =====Mask R-CNN de la Société Matterport===== |
+ | * [[https://github.com/matterport/Mask_RCNN|Mask R-CNN for Object Detection and Segmentation]] sur github | ||
+ | Mask R-CNN is based on Feature Pyramid Network (FPN) and a ResNet101 | ||
+ | * [[https:// | ||
- | [[http://cocodataset.org/#home|COCO is a large-scale object detection, segmentation, | + | ===Feature Pyramid Network=== |
+ | * [[https://arxiv.org/abs/ | ||
- | [[http://cocodataset.org/workshop/coco-mapillary-eccv-2018.html|The goal of the joint COCO and Mapillary Workshop is to study object recognition | + | ===ResNet-101=== |
+ | * [[https://gist.github.com/flyyufelix/65018873f8cb2bbe95f429c474aa1294|ResNet-101 | ||
+ | * [[https:// | ||
- | {{tag>ia python}} | + | {{tag> ia python |
computer_vision_and_pattern_recognition_segmentation_d_image.txt · Dernière modification : 2020/12/27 15:04 de serge