The project is regarding deep learning adn in sub domain of artificial intelligence. The system would take a picture with the help of a camera and feed it to a raspberry pi.that would detect objects present within that image and be able to localize them as well using a convolutional neural network.
Design and Implementation of Convolutional Neural Networks Based Image Extraction
The project is regarding deep learning adn in sub domain of artificial intelligence. The system would take a picture with the help of a camera and feed it to a raspberry pi.that would detect objects present within that image and be able to localize them as well using a convolutional neural network.
The aim is to design and train a convolutional neural network to be able to recognize objects within an image. The system would be running on a hardware assembly comprising of raspberry pi,GPU and camera.
Designing a convolutional neural network for the task.
Training the network.
Testing the CNN for the job.
Embedding it into GPU supported system.
System will be able to detect objects within an image.
Applications of Object detection are wide and can be used in industry to improve production by tracing a faulty object and can also be used in logistics for automatic registration of products and record tracking. It can be used in UAV's for defense, agriculture surveillance purpose.
The final deliverable will be in the form of hardware running convolutional neural network and camera, that would be able to detect objects.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| NVIDIA GTX 1060 | Equipment | 1 | 30000 | 30000 |
| Raspberry Pi | Equipment | 1 | 18000 | 18000 |
| camera | Equipment | 1 | 10000 | 10000 |
| Total in (Rs) | 58000 |
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