Explore semantic segmentation techniques in computer vision through this comprehensive lecture. Delve into key concepts including pretrained layers, skip layers, and up-sampling methods such as nearest neighbor, bilinear interpolation, max unpooling, and deconvolution. Examine sample images and results to understand the practical applications of these techniques in image analysis and object recognition.