Top "Conv-neural-network" questions

A convolutional neural network (CNN, or ConvNet) is a class of deep, feed-forward artificial neural networks that has successfully been applied to analyzing visual imagery.

Fully-connected layer weight dimensions in TensorFlow ConvNet

I've been coding along this example of a convolution net in TensorFlow and I'm mystified by this allocation of weights: …

convolution tensorflow conv-neural-network
How many images(minimum) should be there in each classes for training YOLO?

I am trying to implement YOLOv2 on my custom dataset. Is there any minimum number of images required for each …

conv-neural-network object-detection yolo
TensorFlow ValueError: Variable does not exist, or was not created with tf.get_variable()

I am a newbie to Tensorflow and trying to implement a Generative Adversarial Network. I am following this tutorial for …

python tensorflow optimization conv-neural-network mnist
Random cropping and flipping in convolutional neural networks

In a lot of research papers I read about Convolutional Neural Networks (CNN), I see that people randomly crop a …

image-processing neural-network conv-neural-network
Tensorflow model zoo?

One of the main advantages of caffe for me was the possibility of doing transfer learning on freely distributed pretrained …

machine-learning neural-network tensorflow conv-neural-network
Why should we use Temperature in softmax?

I'm recently working on CNN and I want to know what is the function of temperature in softmax formula? and …

python machine-learning deep-learning conv-neural-network softmax
what does arg_scope actually do?

I am a beginner in neural nets and TensorFlow, and I am trying to understand the role of arg_scope. …

python tensorflow neural-network conv-neural-network
What does global pooling do?

I recently found the "global_pooling" flag in the Pooling layer in caffe, however was unable to find sth about …

image-processing machine-learning deep-learning caffe conv-neural-network
For what reason Convolution 1x1 is used in deep neural networks?

I'm looking at InceptionV3 (GoogLeNet) architecture and cannot understand why do we need conv1x1 layers? I know how convolution …

neural-network tensorflow deep-learning convolution conv-neural-network