Answers.Body: <p>Yes, you can train a NN to detect only one type of object like a table. However, you probably will not want to train such a NN from scratch by showing some examples of tables and non-tables. You will need to use <strong>transfer learning</strong> on a model already trained on several image classes and teach it to also recognize your new class. This transfer learning requires a smaller set of desired images. You may need to give it some negative examples also. You should explore transfer learning with <strong>mobilenet</strong>, <strong>inception</strong>, and other <strong>pre-trained Tensorflow models</strong> if you are willing to use <strong>Python</strong> and Tensorflow</p>
  
Answers.ContentLicense: CC BY-SA 3.0
Answers.CreationDate: 2018-03-02T08:29:16.080Z
Answers.LastActivityDate: 2018-03-02T08:29:16.080Z
Answers.UserDisplayName: Adnan S
Body: <p>I am new to neural networks. Is it possible to train a neural network to identify only one type of object? For instance, a table from a large set of images, where the neural network should be able to identify if new images are tables.</p>
  
Tags: <neural-networks><deep-learning><computer-vision><classification>
Title: Is it possible to train a neural network to identify only one type of object?
UserDisplayName: Th3Nic3Guy
ThreadText: # Is it possible to train a neural network to identify only one type of object?
  
  (Asked by: username_0 on 2018-02-16)
  
  I am new to neural networks. Is it possible to train a neural network to identify only one type of object? For instance, a table from a large set of images, where the neural network should be able to identify if new images are tables.
  
  **Tags:** neural-networks, deep-learning, computer-vision, classification
  
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  ## 1 answers
  
  ### Answer by username_1 on 2018-03-02. Score: 2 | Accepted answer
  
  Yes, you can train a NN to detect only one type of object like a table. However, you probably will not want to train such a NN from scratch by showing some examples of tables and non-tables. You will need to use **transfer learning** on a model already trained on several image classes and teach it to also recognize your new class. This transfer learning requires a smaller set of desired images. You may need to give it some negative examples also. You should explore transfer learning with **mobilenet**, **inception**, and other **pre-trained Tensorflow models** if you are willing to use **Python** and Tensorflow
  
  
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