Skip to main content

Questions tagged [residual-networks]

For questions related to residual networks (ResNets), introduced in "Deep Residual Learning for Image Recognition" (2015) by Kaiming He et al. and that won the first place at "Large Scale Visual Recognition Challenge 2015" (ILSVRC2015).

10 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
3 votes
0 answers
36 views

Why actual mapping is called as unreferenced mapping in this context of residual framework?

Consider the following statements from the research paper titled Deep Residual Learning for Image Recognition by Kaiming He et al. #1: We explicitly reformulate the layers as learning residual ...
hanugm's user avatar
  • 3,890
3 votes
0 answers
635 views

How to use residual learning applied to fully connected networks?

Is there any reason why skip connections would not provide the same benefits to fully connected layers as it does for convolutional? I've read the ResNet paper and it says that the applications should ...
rocksNwaves's user avatar
2 votes
0 answers
46 views

Can Inception-ResNet be inverted layer-by-layer?

It has already been shown that by using a normalization layer during training, it is possible to invert a residual network layer-by-layer. I wonder how similar Inception-ResNet is and whether a ...
Richie Bendall's user avatar
2 votes
0 answers
43 views

How to implement a (3 + 2)-dimensional convolutional layer where the 2d space is "internal"?

I am trying to train a CNN to learn 5D (kind of) data. The data is structured as follows. It has three spatial dimensions [x, y, z], but it also has two "...
play's user avatar
  • 133
1 vote
0 answers
433 views

What are the benefits of Cross Stage Partial Connections over Residual Connections?

Cross Stage Partial Connections (CSPC) try to solve the next problems: Reduce the computations of the model in order to make it more suitable for edge devices. Reduce memory usage. Better ...
IgnacioGaBo's user avatar
0 votes
0 answers
24 views

Why the architeture of Resnet18 is suitable to images classification?

I am studying convolutional networks and in particular I have focused on the ResNet18 network. I've been studying ResNet18 and understand the purpose of skip connections and residual network. However,...
Domme's user avatar
  • 1
0 votes
0 answers
31 views

Attention module (CBAM) in CNN tend to saturate values to 1

In the context of image classification, I am using a feature extractor based on a resnet-like architecture (ResNet12): four residual blocks, each of which is made of two consecutive conv3x3, batch ...
Lorenzo's user avatar
0 votes
0 answers
12 views

Training ImageNet on Resnet - Dropping LR has little improvement on accuracy

I'm trying to train Resnet50 on Imagenet following this paper [1] as well as this one[2]. They say that at approximately every 30 epochs, I should drop the learning rate by 10. Since I'm training on 8 ...
Liam F-A's user avatar
0 votes
0 answers
23 views

Discussion about Improving Visual Search Model Accuracy

My Visual Search Model is only achieving an accuracy of about 42% If anyone can give me advice to drastically improve this number I would greatly appreciate it. Below is my current flow of image ...
rileylivingston's user avatar
0 votes
1 answer
83 views

What underlying network is typically meant with ResNET?

When people talk about a ResNet architecture, they are talking about a neural network architecture with skip connections. But what basis network are they typically referring to? Feedforward-networks ...
postnubilaphoebus's user avatar