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MP Wiki
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Getting started
Introduction
Overview of topics
How to contribute
General best practices
Model families
Classifier / Tagger
Semantic Segmentor
Object Detector
Instance Segmentor
Attributor
Model architectures
ResNet
Faster R-CNN
Mask R-CNN
DeepLabv3+
U-Net
FBNetV3
U-Net++
Efficient Net
PAN
PSPNet
LinkNet
FPN
RetinaNet
Cascade RCNN
FBNetV3IS
FBNetV3OD
CascadeMask R-CNN
Metrics
Confusion Matrix
Intersection over Union (IoU)
Accuracy
Hamming score
Precision
Recall
Precision-Recall curve and AUC-PR
F-beta score
Average Precision
mean Average Precision (mAP)
Loss
Cross-Entropy Loss
Binary Cross-Entropy Loss
Focal loss
Bounding Box Regression Loss
CrossEntropyIoULoss2D
Solvers / Optimizers
Epsilon Coefficient
Momentum (SGD)
Dampening (SGD)
Adam
AMSgrad Variant (Adam)
Adadelta
Adagrad
AdaMax
Adamw
ASGD
Base Learning Rate
Rprop
RMSprop
SGD
Weight Decay
Training Parameters
Patience
Min delta
Seed
Batch Size
Iterations
Epoch
Scheduler
Warm-up
CyclicLR
MultiStepLR
StepLR
CosineAnnealingLR
ReduceLROnPlateau
ExponentialLR
Augmentations
Horizontal Flip
Vertical Flip
Random Crop
Random Sized Crop
Rotate
Resize
Blur
Smallest max size
Center Crop
Color Jitter
Gaussian Noise
Shift Scale Rotate
Longest Max Size
Equalize
To gray
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Deployment
Primitive deployment using web frameworks
Commonly used web frameworks
Containerized Deployment
Orchestrated Deployment
Challenges of Deployment
Splits
General Information
Random
Stratification
Getting started
Introduction
Overview of topics
How to contribute
General best practices
Model families
Classifier / Tagger
Semantic Segmentor
Object Detector
Instance Segmentor
Attributor
Model architectures
ResNet
Faster R-CNN
Mask R-CNN
DeepLabv3+
U-Net
FBNetV3
U-Net++
Efficient Net
PAN
PSPNet
LinkNet
FPN
RetinaNet
Cascade RCNN
FBNetV3IS
FBNetV3OD
CascadeMask R-CNN
Metrics
Confusion Matrix
Intersection over Union (IoU)
Accuracy
Hamming score
Precision
Recall
Precision-Recall curve and AUC-PR
F-beta score
Average Precision
mean Average Precision (mAP)
Loss
Cross-Entropy Loss
Binary Cross-Entropy Loss
Focal loss
Bounding Box Regression Loss
CrossEntropyIoULoss2D
Solvers / Optimizers
Epsilon Coefficient
Momentum (SGD)
Dampening (SGD)
Adam
AMSgrad Variant (Adam)
Adadelta
Adagrad
AdaMax
Adamw
ASGD
Base Learning Rate
Rprop
RMSprop
SGD
Weight Decay
Training Parameters
Patience
Min delta
Seed
Batch Size
Iterations
Epoch
Scheduler
Warm-up
CyclicLR
MultiStepLR
StepLR
CosineAnnealingLR
ReduceLROnPlateau
ExponentialLR
Augmentations
Horizontal Flip
Vertical Flip
Random Crop
Random Sized Crop
Rotate
Resize
Blur
Smallest max size
Center Crop
Color Jitter
Gaussian Noise
Shift Scale Rotate
Longest Max Size
Equalize
To gray
Shear
Deployment
Primitive deployment using web frameworks
Commonly used web frameworks
Containerized Deployment
Orchestrated Deployment
Challenges of Deployment
Splits
General Information
Random
Stratification
MP Wiki
Categories
Getting started
Introduction
Overview of topics
How to contribute
General best practices
Model families
Classifier / Tagger
Semantic Segmentor
Object Detector
Instance Segmentor
Attributor
Model architectures
ResNet
Faster R-CNN
Mask R-CNN
DeepLabv3+
U-Net
FBNetV3
U-Net++
Efficient Net
PAN
PSPNet
LinkNet
FPN
RetinaNet
Cascade RCNN
FBNetV3IS
FBNetV3OD
CascadeMask R-CNN
Metrics
Confusion Matrix
Intersection over Union (IoU)
Accuracy
Hamming score
Precision
Recall
Precision-Recall curve and AUC-PR
F-beta score
Average Precision
mean Average Precision (mAP)
Loss
Cross-Entropy Loss
Binary Cross-Entropy Loss
Focal loss
Bounding Box Regression Loss
CrossEntropyIoULoss2D
Solvers / Optimizers
Epsilon Coefficient
Momentum (SGD)
Adam
Adadelta
Adagrad
AdaMax
Adamw
ASGD
Base Learning Rate
Rprop
RMSprop
SGD
Weight Decay
Training Parameters
Patience
Min delta
Seed
Batch Size
Iterations
Epoch
Scheduler
Warm-up
CyclicLR
MultiStepLR
StepLR
CosineAnnealingLR
ReduceLROnPlateau
ExponentialLR
Augmentations
Horizontal Flip
Vertical Flip
Random Crop
Random Sized Crop
Rotate
Resize
Blur
Smallest max size
Center Crop
Color Jitter
Gaussian Noise
Shift Scale Rotate
Longest Max Size
Equalize
To gray
Shear
Deployment
Primitive deployment using web frameworks
Commonly used web frameworks
Containerized Deployment
Orchestrated Deployment
Challenges of Deployment
Splits
General Information
Random
Stratification
Removing the risk from vision AI.
Only 13% of vision AI projects make it to production, with Hasty we boost that number to 100%.
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