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.
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-networkI am trying to implement YOLOv2 on my custom dataset. Is there any minimum number of images required for each …
conv-neural-network object-detection yoloI 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 mnistIn 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-networkOne 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-networkI am using VGG16 with keras for transfer learning (I have 7 classes in my new model) and as such I …
python machine-learning keras conv-neural-network pre-trained-modelI'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 softmaxI 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-networkI 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-networkI'm looking at InceptionV3 (GoogLeNet) architecture and cannot understand why do we need conv1x1 layers? I know how convolution …
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