/en/tags/gan/Recent content in GAN on Mi&Bee BlogHugo -- gohugo.ioen蓝宝石的傻话Sat, 20 Jun 2026 10:00:00 +0800/en/posts/physical-world/dl-super-resolution-srcnn-srgan/Sat, 20 Jun 2026 10:00:00 +0800/en/posts/physical-world/dl-super-resolution-srcnn-srgan/<h2 id="from-mathematical-models-to-data-driven-learning">From Mathematical Models to Data-Driven Learning</h2> <p>In super-resolution tasks, traditional methods rely on carefully designed mathematical models—interpolation algorithms, sparse representation, prior constraints, and so on. But deep learning brought a paradigm shift: directly learning the mapping from degraded space to clear space from massive paired low-resolution (LR) and high-resolution (HR) image data.</p> <p>The core idea is simple: train a neural network $F_{\theta}$ that can map low-resolution images to high-resolution images:</p>