this project demonstrate the problem and effects of Landmines In Defense Field.We are proposing a vehicle that has the aptitude to detect landminesand lets user can control the vehicle Manually to avoid casualties.We will use the technique for the detection of buried Landmineswith thermal infrared I
Landmines Detection Robotic Vehicle Using Deep Learning
this project demonstrate the problem and effects of Landmines In Defense Field.We are proposing a vehicle that has the aptitude to detect landminesand lets user can control the vehicle Manually to avoid casualties.We will use the technique for the detection of buried Landmineswith thermal infrared Imaging. In this project we will focus on the safety of humans using deep learning.In deep Learning a computer Model leran to perform classifictions usnig deep learning directly images taken from camera using Mask Region Based Convolutional Network(Mask-RCNN) method for buried Landmines Detection.When the object is detected on or below the surface of earth our intelligent system will detect mines by taking images using cameras.
The objectives are:
1-A landmines detection vehicle is needed to be design to employ in peace support operations.
2- To clear dangerous Areas
3-For the safety of operator .
Thermography method it has the ability to detect Land Mines which are buried underground.Then we will apply Mask Rcnn lgorithm to detect ithe images.by comparing it from Dataset.
Benefits are:
1:for the safety Of people
2:For Armed services
3:Line of control
4:Patrolling in Dangerous Areas.
Our project will be completed at the end of june so far we have build a vehicle .and we have completed the Fast RcNN to detect the images taken from camera after that we are going to implement Mask RCNN gfor the bounding box of imges.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Thermal Camera | Equipment | 1 | 7000 | 7000 |
| RGB Camera | Equipment | 1 | 1000 | 1000 |
| Chasis Of Vehicle | Equipment | 1 | 1100 | 1100 |
| RaspberryPi | Equipment | 1 | 6500 | 6500 |
| GPU | Equipment | 1 | 32000 | 32000 |
| DC Batteries | Equipment | 4 | 200 | 800 |
| Total in (Rs) | 48400 |
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