17 items
Real-World Computer Vision Applications
Common CV Challenges
Evaluation Metrics: IoU and mAP
Transfer Learning with Pretrained Vision Models
Image Segmentation: Semantic vs Instance
Object Detection and Bounding Boxes
Image Classification Task
Edge Detection and Classical Features
CNN Architecture for Vision Tasks
Pooling Layers and Downsampling
Feature Maps and Learned Visual Features
Convolution and Kernels Explained
Image Augmentation Techniques
Image Preprocessing Essentials
Color Spaces: RGB, Grayscale, HSV
How Digital Images Are Represented
What Computer Vision Is
Image classification assigns a single label to an entire image from a fixed set of categories.
