Explore extreme low-light imaging techniques in this 31-minute lecture from the University of Central Florida. Delve into the challenges of capturing images in near-dark conditions and learn about innovative solutions using deep learning approaches. Examine the See-in-the-Dark Dataset, camera setups, and amplification factors. Understand the intricacies of Bayer arrays and X-Trans sensors. Study the network architecture and training process of a ConvNet Block UNet model. Analyze experimental results comparing traditional methods, denoising techniques like BM3D, and smartphone capabilities. Gain insights into evaluation metrics and quantitative outcomes for improving low-light photography and imaging technologies.