Welcome to the Computer Vision Course of InstaDataHelp Analytics Services, a captivating exploration of the extraordinary world where machines gain the ability to perceive, interpret, and understand visual information, much like the human eye and brain. Computer Vision is the driving force behind technologies like autonomous vehicles, medical image analysis, facial recognition, and so much more, revolutionizing industries across the globe.
This course serves as your portal into the captivating domain of Computer Vision, where you’ll unravel the theoretical foundations and master practical techniques. Whether you’re a budding computer scientist, an aspiring data analyst, or a seasoned engineer, the skills you’ll acquire here are essential in today’s data-driven world.
Our journey begins with the fundamentals, covering image processing techniques, feature extraction, and image transformations. We’ll then delve into the power of deep learning, exploring Convolutional Neural Networks (CNNs) for image analysis and object detection.
But Computer Vision doesn’t stop at images—it extends to videos and 3D environments. We’ll venture into object tracking, motion analysis, and 3D reconstruction, enabling you to perceive the dynamic aspects of visual data.
By course completion, you’ll be equipped with the skills to create intelligent systems that can see, understand, and make decisions based on visual inputs. Join us on this exhilarating expedition into the realm of Computer Vision, where you’ll unlock the potential to build groundbreaking applications and contribute to the forefront of artificial intelligence. Let’s embark on this visual journey together!
Please find the course curriculum for the Computer Vision course.
Week 1: Introduction to Computer Vision
- Day 1: Course overview and importance of Computer Vision
- Day 2: History and evolution of Computer Vision
- Day 3: Basic principles and challenges
- Day 4: Image representation and color spaces
- Day 5: Hands-on lab – Image loading and visualization
Week 2: Image Processing
- Day 6: Image enhancement techniques (brightness, contrast, sharpening)
- Day 7: Filtering and convolution operations
- Day 8: Edge detection and feature extraction
- Day 9: Image segmentation and region-based processing
- Day 10: Hands-on lab – Image processing techniques
Week 3: Image Features and Descriptors
- Day 11: Key points and interest operators (Harris, FAST, SIFT)
- Day 12: Local image descriptors (SIFT, SURF, ORB)
- Day 13: Feature matching and recognition
- Day 14: Scale-invariant features
- Day 15: Hands-on lab – Feature detection and matching
Week 4: Image Transformations
- Day 16: Geometric transformations (rotation, scaling, translation)
- Day 17: Affine transformations and homographies
- Day 18: Image warping and panoramic image stitching
- Day 19: Projective geometry and camera models
- Day 20: Hands-on lab – Image transformations and stitching
Week 5: Deep Learning for Computer Vision
- Day 21: Introduction to Convolutional Neural Networks (CNNs)
- Day 22: Building and training CNNs using deep learning frameworks
- Day 23: Transfer learning and pre-trained models
- Day 24: Object detection with CNNs (YOLO, SSD)
- Day 25: Hands-on lab – Building and training CNNs
Week 6: Object Tracking and Motion Analysis
- Day 26: Object tracking methods (KLT, Mean-Shift, GOTURN)
- Day 27: Optical flow and motion estimation
- Day 28: Kalman filters and particle filters
- Day 29: Multiple object tracking
- Day 30: Hands-on lab – Object tracking and motion analysis
Week 7: 3D Computer Vision
- Day 31: Stereopsis and depth perception
- Day 32: Structure from Motion (SfM)
- Day 33: 3D reconstruction and point cloud processing
- Day 34: Camera calibration and pose estimation
- Day 35: Hands-on lab – 3D reconstruction and depth estimation
Week 8: Advanced Topics
- Day 36: Deep learning for semantic segmentation
- Day 37: Object recognition and image retrieval
- Day 38: Face detection and recognition
- Day 39: Augmented reality and Computer Vision applications
- Day 40: Course review and future directions
Week 9: Final Projects and Presentations
- Students work on their Computer Vision projects
- Guidance and support from the instructor
- Final project presentations and peer evaluations
The course structure and duration is suggestive. For customized course, please contact us. We will be providing customized course which will be suitable for your organizational goal.
Please contact at info@instadatahelp.com or call at +91 9903726517 to know further about the course.
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