Answers.Body: <p>That's definitely possible with <strong>Convolutional Neural Networks</strong>. You should follow Google's tutorial at:</p>
  
  <blockquote>
    <p><a href="https://www.tensorflow.org/tutorials/deep_cnn#cifar-10_model" rel="nofollow noreferrer">https://www.tensorflow.org/tutorials/deep_cnn#cifar-10_model</a></p>
  </blockquote>
  
  <p>The tutorial will teach you how to build a deep learning model for classifying cars, trucks etc. It's an easy tutorial to follow.</p>
  
  <p>Your model will build on images pixels. The classifier will know what a car looks like.</p>
  
  <p><a href="https://i.sstatic.net/5BEx4.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/5BEx4.png" alt="enter image description here"></a></p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2017-05-08T11:15:35.990Z
Answers.LastActivityDate: 2017-05-08T11:15:35.990Z
Answers.UserDisplayName: SmallChess
Body: <p>I would like to use deep leaning for identifying cars; I want the system to predict wether an object is a car or not. How can I do that knowing that im still a beginner in the Deep Learning field ?
  I am considering visual recognition. The system must recognize the car from anything else on the road.</p>
  
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-05-08T14:17:04.000Z
Comments.Text: The first thing you should consider is about the recognition -- are you considering visual, audio, olfactory, ..l recognition? And, assuming audio, are you recognizing cars vs. what, everything? Recognizing cars from e.g. trucks is much different than recognizing cars from silence. And this is just the beginning. The point is that the question has to be better defined if you want a meaningful answer
Comments.UserDisplayName: Teusz
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-05-08T14:18:42.330Z
Comments.Text: @Teusz That doesn't make any sense. The point of deep-learning is to provide a huge data set for the model to figure out how to classify a car vs a truck. There is no need to consider audio from a car image. Your comment is wrong and misleading.
Comments.UserDisplayName: SmallChess
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-05-08T14:19:44.720Z
Comments.Text: Identification need not be performed only with basis on image data. Possible also to recognize from audio (or audio-visual) data.
Comments.UserDisplayName: Teusz
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-05-08T14:50:23.557Z
Comments.Text: @Teusz Well... The question is about "an object is a car or not". OP didn't ask if the sound come from a car or a truck. I still believe your comment is wrong.
Comments.UserDisplayName: SmallChess
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-05-08T15:20:30.780Z
Comments.Text: Sound can be used to classify objects -- that's the entire field of acoustic event detection. Check it out!
Comments.UserDisplayName: Teusz
Comments.ContentLicense: CC BY-SA 3.0
Comments.CreationDate: 2017-07-24T18:30:11.897Z
Comments.Text: @SmallChess you have been lost in small wires of the internet.hahaha....However,the. OP is kinda a beginner..And one shouldn't complex concepts here,because computer vision is wide.
Comments.UserDisplayName: quintumnia
Tags: <deep-learning><object-recognition>
Title: Identifying cars using deep learning
UserDisplayName: F.Lin
ThreadText: # Identifying cars using deep learning
  
  (Asked by: username_0 on 2017-05-08)
  
  I would like to use deep leaning for identifying cars; I want the system to predict wether an object is a car or not. How can I do that knowing that im still a beginner in the Deep Learning field ?
  I am considering visual recognition. The system must recognize the car from anything else on the road.
  
  **Tags:** deep-learning, object-recognition
  
  > **Comments:**
  > **username_1**: The first thing you should consider is about the recognition -- are you considering visual, audio, olfactory, ..l recognition? And, assuming audio, are you recognizing cars vs. what, everything? Recognizing cars from e.g. trucks is much different than recognizing cars from silence. And this is just the beginning. The point is that the question has to be better defined if you want a meaningful answer  
  > **username_2**: @username_1 That doesn't make any sense. The point of deep-learning is to provide a huge data set for the model to figure out how to classify a car vs a truck. There is no need to consider audio from a car image. Your comment is wrong and misleading.  
  > **username_1**: Identification need not be performed only with basis on image data. Possible also to recognize from audio (or audio-visual) data.  
  > **username_2**: @username_1 Well... The question is about "an object is a car or not". OP didn't ask if the sound come from a car or a truck. I still believe your comment is wrong.  
  > **username_1**: Sound can be used to classify objects -- that's the entire field of acoustic event detection. Check it out!  
  > **username_3**: @username_2 you have been lost in small wires of the internet.hahaha....However,the. OP is kinda a beginner..And one shouldn't complex concepts here,because computer vision is wide.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2017-05-08. Score: 1 | Accepted answer
  
  That's definitely possible with **Convolutional Neural Networks**. You should follow Google's tutorial at:
  
  > <https://www.tensorflow.org/tutorials/deep_cnn#cifar-10_model>
  
  The tutorial will teach you how to build a deep learning model for classifying cars, trucks etc. It's an easy tutorial to follow.
  
  Your model will build on images pixels. The classifier will know what a car looks like.
  
  [![enter image description here](https://i.sstatic.net/5BEx4.png)](https://i.sstatic.net/5BEx4.png)
  
  
  ---
  
  