https://111qqz.com/en/tags/resnet/Recent content in Resnet on 111qqz's blogHugo -- gohugo.ioen© 2015-2026 111qqzSun, 05 Apr 2020 16:49:44 +0800https://111qqz.com/en/post/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E8%AE%A1%E7%AE%97%E6%9C%BA%E8%A7%86%E8%A7%89/2020-04-05-resnet-notes/Sun, 05 Apr 2020 16:49:44 +0800https://111qqz.com/en/post/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E8%AE%A1%E7%AE%97%E6%9C%BA%E8%A7%86%E8%A7%89/2020-04-05-resnet-notes/<h2 class="relative group">背景 <div id="背景" class="anchor"></div> <span class="absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none"> <a class="text-primary-300 dark:text-neutral-700 !no-underline" href="#%e8%83%8c%e6%99%af" aria-label="Anchor">#</a> </span> </h2> <p>基于Conv的方法在某年的ImageNet比赛上又重新被人想起之后，大家发现网络堆叠得越深，似乎在cv的各个任务上表现的越好。</p>https://111qqz.com/en/post/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E8%AE%A1%E7%AE%97%E6%9C%BA%E8%A7%86%E8%A7%89/2017-07-18-inception-resnet-notes/Tue, 18 Jul 2017 02:42:50 +0000https://111qqz.com/en/post/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0/%E8%AE%A1%E7%AE%97%E6%9C%BA%E8%A7%86%E8%A7%89/2017-07-18-inception-resnet-notes/<p><a href="https://arxiv.org/abs/1602.07261" target="_blank" rel="noreferrer">原始论文</a></p> <p><a href="https://ask.julyedu.com/question/7711" target="_blank" rel="noreferrer">翻译链接</a></p> <blockquote><p>**——前言：**作者认为残差连接在训练深度卷积模型是很有必要的。至少在图像识别上，我们的研究似乎并不支持这一观点。</p>