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Caffe | Hinge Loss Layer - Berkeley Vision

http://caffe.berkeleyvision.org/tutorial/layers/hingeloss.html

Caffe. Deep learning framework by BAIR. Created by Yangqing Jia Lead Developer Evan Shelhamer. View On GitHub; Hinge (L1, L2) Loss Layer


Caffe | Layer Catalogue - Berkeley Vision

http://caffe.berkeleyvision.org/tutorial/layers.html

It’s conceptually identical to a softmax layer followed by a multinomial logistic loss layer, but provides a more numerically stable gradient. Sum-of-Squares / Euclidean - computes the sum of squares of differences of its two inputs, . Hinge / Margin - The hinge loss layer computes a one-vs-all hinge (L1) or squared hinge loss (L2).


caffe/layers.md at master · intel/caffe · GitHub

https://github.com/intel/caffe/blob/master/docs/tutorial/layers.md


caffe/hinge_loss_layer.cpp at master · BVLC/caffe · GitHub

https://github.com/BVLC/caffe/blob/master/src/caffe/layers/hinge_loss_layer.cpp

Dtype* loss = top[0]-> mutable_cpu_data (); switch (this-> layer_param_. hinge_loss_param (). norm ()) {case HingeLossParameter_Norm_L1: loss[0] = caffe_cpu_asum (count, bottom_diff) / …


Caffe | Loss

https://caffe.berkeleyvision.org/tutorial/loss.html

However, any layer able to backpropagate may be given a non-zero loss_weight, allowing one to, for example, regularize the activations produced by some intermediate layer(s) of the network …


Caffe | Layer Catalogue - Berkeley Vision

http://tutorial.caffe.berkeleyvision.org/tutorial/layers.html

To create a Caffe model you need to define the model architecture in a protocol buffer definition file (prototxt). Caffe layers and their parameters are defined in the protocol buffer definitions …


Trying to understand custom loss layer in caffe

https://stackoverflow.com/questions/44674480/trying-to-understand-custom-loss-layer-in-caffe

I have seen one can define a custom loss layer for example EuclideanLoss in caffe like this: import caffe import numpy as np class EuclideanLossLayer(caffe.Layer): """ Compute...


c++ - caffe layer loss_weight_size - Stack Overflow

https://stackoverflow.com/questions/39892887/caffe-layer-loss-weight-size


c++ - Euclidean Loss Layer in Caffe - Stack Overflow

https://stackoverflow.com/questions/31099233/euclidean-loss-layer-in-caffe

1 Answer. For loss layers, there is no next layer, and so the top diff blob is technically undefined and unused - but Caffe is using this preallocated space to store unrelated …


Hinge loss - Wikipedia

https://en.wikipedia.org/wiki/Hinge_loss

The hinge loss is a convex function, so many of the usual convex optimizers used in machine learning can work with it. It is not differentiable, but has a subgradient with respect to model parameters w of a linear SVM with score function that is …


marcelsimon/mycaffe: Modified caffe with some added layers ...

http://triton.inf-cv.uni-jena.de/marcelsimon/mycaffe/src/fa7fda78661fa795e3f6d3bbe7040e5d5d02e732/include/caffe/layers/hinge_loss_layer.hpp?lang=en-US

hinge_loss_layer.hpp. hinge_loss_layer.hpp 4.2 KB. History Raw

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