Body: <p>This is a follow-up question from my previous post <a href="https://ai.stackexchange.com/questions/16444">here</a> about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best suits this problem, given that here we have a cloud of smoke/fire as opposed to an object. Any suggestions?</p>
  
  <p>For instance, I've learned about Faster RCNN or RetinaNet, but that is mostly for <strong>object</strong> detection. Is it going to be better than say a basic ResNet50? And here real-time prediction requirements are not an issue. So shall I assume a heavier model (e.g. NASNet Large or a Resnet-152 model) is better than a basic ResNet-50 model?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-13T13:01:20.623Z
Comments.Text: "I gathered a dataset of explosions", have you found it on the web or have you manually created it? If you found it on the web, maybe you can give an answer to your other question.
Comments.UserDisplayName: nbro
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-13T17:54:43.253Z
Comments.Text: No I created a small dataset myself from youtube! Had a hard time.
Comments.UserDisplayName: Mary
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2019-11-14T02:12:19.957Z
Comments.Text: In case you do not find a specific architecture suited for your problem, I would suggest you start with the simplest architecture. If it doesn't perform well enough, try with a more complex one, and so on.
Comments.UserDisplayName: nbro
Tags: <machine-learning><deep-learning><keras><deep-neural-networks><models>
Title: Which deep neural networks are appropriate for the detection of bombs?
UserDisplayName: Mary
ThreadText: # Which deep neural networks are appropriate for the detection of bombs?
  
  (Asked by: username_0 on 2019-11-13)
  
  This is a follow-up question from my previous post [here](https://ai.stackexchange.com/questions/16444) about explosion detection. I gathered a dataset of explosions. As I'm new to Deep Learning in Keras, I'm trying to see what architecture best suits this problem, given that here we have a cloud of smoke/fire as opposed to an object. Any suggestions?
  
  For instance, I've learned about Faster RCNN or RetinaNet, but that is mostly for **object** detection. Is it going to be better than say a basic ResNet50? And here real-time prediction requirements are not an issue. So shall I assume a heavier model (e.g. NASNet Large or a Resnet-152 model) is better than a basic ResNet-50 model?
  
  **Tags:** machine-learning, deep-learning, keras, deep-neural-networks, models
  
  > **Comments:**
  > **username_1**: "I gathered a dataset of explosions", have you found it on the web or have you manually created it? If you found it on the web, maybe you can give an answer to your other question.  
  > **username_0**: No I created a small dataset myself from youtube! Had a hard time.  
  > **username_1**: In case you do not find a specific architecture suited for your problem, I would suggest you start with the simplest architecture. If it doesn't perform well enough, try with a more complex one, and so on.  
  
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  ## 0 answers
  
  