Automatic Target recognition using Deep Learning Techniques
In this project, we have implemented a deep learning model that can automatically recognize the target in an image. Deep learning has evolved a lot over the past few years, it is reliable and can be used in real world applications. It is all made possible due to digital world that is generat
2025-06-28 16:25:27 - Adil Khan
Automatic Target recognition using Deep Learning Techniques
Project Area of Specialization Artificial IntelligenceProject SummaryIn this project, we have implemented a deep learning model that can automatically recognize the target in an image. Deep learning has evolved a lot over the past few years, it is reliable and can be used in real world applications. It is all made possible due to digital world that is generating huge amount data per day, efficient deep learning algorithms and fast computers. Object detection involves two things i.e. classification and localization. It means that what is name of the object and where it is located in the image. It can be done by drawing the bounding box around the object and labelling its name on top of the bounding box. To do this we need to train a deep learning model of our choice on our custom dataset. And once the model is trained then it will be to detect those custom multiple objects in the image/video. Detection can also be done in real time as well. We have performed detection on 5 classes using deep learning model called YOLOv4 on Google Colab (Cloud GPUs).
Project Objectives- Implementation of an automatic target recognition system.
- Recognition of target using deep learning technique.
- Created custom datatset.
- Labelled it using "labelImg".
- Cloned the deep learning algorithm YOLOv4.
- Trained the YOLOv4 on our custom datatset on Google Colab.
Object detection is one of the important components of many vision systems.
It has numerous applications in:
• Traffic control
• Human- computer interaction
• Digital forensics
• Gesture recognition
• Augmented reality
• Visual surveillance
Following are the techinacal deliverables:
- Trained AI Model of around 5500 images of 5 classes.
- Script for Training on goole collab.
- Custom made data set of 5500 Images of 5 classes.
- Detailed Theisis Report.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 7625 | |||
| Google Colab pro account | Equipment | 1 | 3625 | 3625 |
| Report Binding | Miscellaneous | 2 | 2000 | 4000 |