Image Recognition Using CIFAR 10
- 1. Image Recognition Using CIFAR-10 INDUSTRY ORIENTED MINI PROJECT PRESENTATION
- 2. Topics: • Introduction • What is Image Recognition? • What is CIFAR-10? • What is there in this project? • What did I do in this project? • Process(How does it work?) • How the result is obtained? • Conclusion
- 3. Introduction ARTIFICIAL INTELLIGENCE WHAT COMES INTO YOUR MIND?
- 6. Here the point is….. IMAGE RECOGNITION
- 7. What is Image Recognition? •It is a technology that is used to recognise an object in the image. •If u show a cat image to the image recognition model. It gives you the output as cat.
- 8. What is CIFAR-10? • The CIFAR-10 is a dataset. • It is a set of images which consists of 60,000 images. • Size 32*32. • These 60,000 images are divided into 10 classes each consisting of 6000 images.
- 9. 10 Classes And 10 random images from each class We use this dataset to train our model and recognise the images.
- 10. What is there in this project? •A model which recognises the images which we trained i.e. using CIFAR-10.
- 11. What did I do in this project? •I used the machine learning concepts to build this model using python programming language. •I used the very basic machine learning concepts like tensorflow and keras. •I trained the model with CIFAR-10 Dataset.
- 12. How does it work? Start Input the image path It processes the image and compares the image with the trained images Checks whether matching or not Stop Shows the output Shows the output with least matching features If matches If does not match
- 13. How the result is obtained? • First of all the image we upload is processed with the images we trained previously and compared with each image of dataset. • Now if maximum number of features are matching then the result is shown as the class name. • If not matching then it checks for least matching features • However it gives the match. • The better the training given to the model.The better the results are!
- 14. Conclusion This is the simple model that shows how does the basic image recognition works and how to work with the basic concepts of machine learning.