Answers.Body: <p>so assuming your not allowed to use transfer methodologies (like take an already exisiting elephant object detector) my recommendation is to train a CNN classifier (labels are binary-- elephant exist, elephant doesnt exist) and then use strategies founded in like <a href="https://arxiv.org/abs/1610.02391" rel="nofollow noreferrer">grad cam</a>. Note there does exist a gradcam++ but because you can assure theres only one instance, it isnt necessary and is just more complicated. </p>
  
  <p>Note that since you just need the location and not the pixel specificity, you dont even need to do the guided backprop, but just the relation with respect to the last convoluitional map.</p>
  
  <p>A quick description is that its using the gradient of the class loss w.r.t the last feature map to see which locations helped make the classification, and from there you can upscale to the receptive field that those neurons touch</p>
  
  <p>Hope this helped!</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-06-24T17:51:57.650Z
Answers.LastActivityDate: 2019-06-24T17:51:57.650Z
Answers.UserDisplayName: mshlis
Body: <p>Some pictures contain an elephant, others don't. I know which of the pictures contain the elephant, but I don't know where it is or how does it look like.  </p>
  
  <p>How do I make a neural network which locates the elephant on a picture if it contains one? There are no pictures with more than one elephant.</p>
  
Tags: <deep-learning><object-detection><semi-supervised-learning>
Title: How do I locate a specific object in an image?
UserDisplayName: user31264
ThreadText: # How do I locate a specific object in an image?
  
  (Asked by: username_0 on 2019-06-24)
  
  Some pictures contain an elephant, others don't. I know which of the pictures contain the elephant, but I don't know where it is or how does it look like.
  
  How do I make a neural network which locates the elephant on a picture if it contains one? There are no pictures with more than one elephant.
  
  **Tags:** deep-learning, object-detection, semi-supervised-learning
  
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  ## 1 answers
  
  ### Answer by username_1 on 2019-06-24. Score: 1 | Accepted answer
  
  so assuming your not allowed to use transfer methodologies (like take an already exisiting elephant object detector) my recommendation is to train a CNN classifier (labels are binary-- elephant exist, elephant doesnt exist) and then use strategies founded in like [grad cam](https://arxiv.org/abs/1610.02391). Note there does exist a gradcam++ but because you can assure theres only one instance, it isnt necessary and is just more complicated.
  
  Note that since you just need the location and not the pixel specificity, you dont even need to do the guided backprop, but just the relation with respect to the last convoluitional map.
  
  A quick description is that its using the gradient of the class loss w.r.t the last feature map to see which locations helped make the classification, and from there you can upscale to the receptive field that those neurons touch
  
  Hope this helped!
  
  
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