Programming a computer and designing algorithms to figure out what is in those images is the field of computer vision. In this article, I will take you through 20 Machine Learning projects on Computer Vision solved and explained with Python programming language.
Machine Learning Projects on Computer Vision
- Lung Segmentation
- Sign Language Classification
- Flower Recognition
- Pneumonia Detection
- Face Mask Detection
- Google Landmark Detection Model
- Age and Gender Detection
- Bar Code and QR Code Reader
- Handwriting Recognition
- Face Detection
- Deepfake Detection
- Pencil Sketch with OpenCV
- Instagram Filters with Python
- Colour Recognition
- Image Features Extraction
- Extract Text from Images
- Image Segmentation
- Image Recognition
- Fashion Recommendation System
- Face Landmarks Detection
What is Computer Vision?
Computer vision is the task of extracting useful information from images. Information can mean anything from 3D models, camera position, object detection and recognition to grouping and searching for image content.
In formulating and solving computer vision problems, the researchers have often found it useful to draw inspiration from three high-level approaches:
- Scientific: Build detailed models of the imaging process and develop mathematical techniques to reverse them to recover quantities of interest.
- Statistics: Use probabilistic models to quantify the a priori probability of your unknowns and the noisy measurement processes that produce the input images, then infer the best possible estimates of your desired quantities and analyze the resulting uncertainties. The inference algorithms used are often closely related to optimization techniques used to reverse (scientific) imaging processes.
- Engineering: develop techniques that are easy to describe and implement but which are also known to work well in practice. Test these techniques to understand their throttling and failure modes, and their expected computational costs.
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