MATLAB Workshop on AI Techniques for Computer Vision
Day 4: MATLAB Workshop on AI Techniques for Computer Vision
On the fourth day, SKIT IEEE SB will be conducting a hands-on workshop in collaboration with MathWorks, focusing on AI techniques for computer vision using MATLAB. This workshop will provide students with practical skills and tools to explore AI solutions in the visual domain, enhancing their understanding of AI applications.
Date and Time
Location
Hosts
Registration
- Date: 04 Oct 2024
- Time: 10:00 AM to 02:30 PM
- All times are (UTC+05:30) Chennai
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- Swami Keshvanand Institute of Technology, Management & Gramothan
- Ramnagaria, Jagatpura
- Jaipur, Rajasthan
- India 302017
- Building: Civil Block
- Room Number: J C Bose Auditorium
- Contact Event Hosts
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IEEE Day Special: MATLAB Workshop at SKIT Jaipur 🎉
📅 Date: 4th October 2024
🕒 Time: 09:30 AM - 2:30 PM
📍 Venue: JC Bose Auditorium💡 Hurry and register now to secure your spot!
🔗 Register: https://forms.gle/SNEU2GxwoWxuWgDZA
For any queries, feel free to contact us at:
Contact information :
+91-6377829943 (Sanskar)
+91-7425980850 (Ansh)
+91-9772111651(Jagrati) - Co-sponsored by IEEE Rajasthan Subsection
Speakers
Manoj Kumar of Mathworks
AI techniques for computer vision using MATLAB
Event will cover "
Key AI techniques in MATLAB for computer vision include:
1. **Image Classification**: Using deep learning networks like Convolutional Neural Networks (CNNs), MATLAB allows the classification of objects within images. Pre-trained models like AlexNet and ResNet can be fine-tuned for specific tasks, enabling accurate object recognition.
2. **Object Detection**: MATLAB provides tools for detecting objects in images or video streams using techniques like YOLO (You Only Look Once) and Faster R-CNN. These algorithms enable real-time object detection for applications like autonomous driving or security systems.
3. **Semantic Segmentation**: This technique involves classifying each pixel in an image into a category, allowing for detailed understanding of scenes. MATLAB’s deep learning toolbox supports semantic segmentation with networks like U-Net and DeepLab.
4. **Face Recognition and Tracking**: MATLAB facilitates face detection and recognition using machine learning and deep learning models. The system can identify facial landmarks and track faces in real time, useful for security and biometric systems.
5. **Optical Character Recognition (OCR)**: MATLAB allows the extraction of text from images using AI-based OCR algorithms, useful in document digitization and automated data entry processes.
MATLAB simplifies the integration of AI with computer vision through a user-friendly interface, pre-trained models, and extensive support for custom algorithms. This makes it an ideal platform for exploring AI applications in the visual domain."
Biography:
Manoj Kumar is Asst. Manager-Technical at DesignTech Systems Pvt.
Ltd. (@New Delhi office) from past 5+ years. His main focus is to train
MATLAB users on MathWorks products on their required application.
Prior to joining to DesignTech He worked more than 4 years in DBIT
Dehradun as Asst. Professor. He has 2+ years industry experience as
Automation Engineer. He has completed bachelor’s degree in
Electronics & Communications and certification in Advance Course in
Embedded Systems from Vector Institute Hyderabad.
Address:Swami Keshvanand Institute of Technology, Management & Gramothan, Ramnagaria, Jagatpura, Jaipur, India, 302017