Explore advanced edge detection techniques in this comprehensive computer vision lecture. Delve into Prewitt and Sobel edge detectors, understanding their derivative masks and image derivatives. Compare Sobel and Prewitt methods before progressing to second derivative techniques. Examine the Marr-Hildreth edge detector, including LOG filters and zero crossings. Study the Canny edge detector in depth, covering gradient orientation, hysteresis thresholding, and the effects of Gaussian smoothing. Conclude with an introduction to edge detection using deep learning, providing a well-rounded understanding of both classical and modern approaches to this fundamental computer vision task.