Other annotation tool related information - eng

Qingyou__edge detection.zip 39.56MB

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edge detection.zip 大约有4个文件

0730-Industrial Quality Inspection Dataset - Chinese.docx 14.91MB
0730-Industrial Quality Inspection Dataset - eng.docx 5.95MB
Other annotation tool related information - chinese.docx 15.54MB
Other annotation tool related information - eng.docx 3.99MB

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Other annotation tool related information - eng

<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89621169/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89621169/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">其他标注工具相关信息</div><div class="t m0 x1 h3 y2 ff2 fs1 fc0 sc0 ls0 ws0">Dexined<span class="_ _0"> </span><span class="ff1">相关</span></div><div class="t m0 x1 h4 y3 ff3 fs2 fc1 sc0 ls0 ws0">1.<span class="_ _1"> </span><span class="ff4 fs3 fc0">BIPED<span class="_ _2"> </span><span class="ff5">网址：</span>https://xavysp.github.io/MBIPED/</span></div><div class="t m0 x1 h4 y4 ff5 fs3 fc0 sc0 ls0 ws0">描述：<span class="ff4">These images have been carefully annotated by experts on the computer </span></div><div class="t m0 x1 h5 y5 ff4 fs3 fc0 sc0 ls0 ws0">vision field, hence no redundancy has been considered. </div><div class="t m0 x1 h4 y6 ff5 fs3 fc0 sc0 ls0 ws0">翻译：这些图像已经由计算机视觉领域的专家仔细注释，因此没有考虑冗余。</div><div class="t m0 x1 h4 y7 ff5 fs3 fc0 sc0 ls0 ws0">结论：没有提到边缘的标注工具。</div><div class="t m0 x1 h6 y8 ff3 fs2 fc1 sc0 ls0 ws0">2.<span class="_ _1"> </span><span class="ff4 fs3 fc0">Dexined github: https://github.com/xavysp/DexiNed?tab=readme-ov-</span></div><div class="t m0 x1 h5 y9 ff4 fs3 fc0 sc0 ls0 ws0">file#datasets</div><div class="t m0 x1 h4 ya ff5 fs3 fc0 sc0 ls0 ws0">结论：没有提到边缘的标注工具。</div><div class="t m0 x1 h3 yb ff1 fs1 fc0 sc0 ls0 ws0">其他工具</div><div class="t m0 x1 h7 yc ff2 fs4 fc0 sc0 ls0 ws0">1 QT+OpenCV</div><div class="t m0 x1 h4 yd ff3 fs2 fc1 sc0 ls0 ws0">1.<span class="_ _1"> </span><span class="ff4 fs3 fc0">CSDN<span class="_ _2"> </span><span class="ff5">链接：</span>https://blog.csdn.net/FonlinCSDN/article/details/129726446</span></div><div class="t m0 x1 h4 ye ff3 fs2 fc1 sc0 ls0 ws0">2.<span class="_ _1"> </span><span class="ff4 fs3 fc0">github<span class="_ _2"> </span><span class="ff5">链接：</span>https://github.com/FonlinGH/MarkupTool</span></div><div class="t m0 x1 h4 yf ff3 fs2 fc1 sc0 ls0 ws0">3.<span class="_ _1"> </span><span class="ff5 fs3 fc0">可能的问题：需要编译</span></div><div class="t m0 x1 h6 y10 ff3 fs2 fc1 sc0 ls0 ws0">4.</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div><div id="pf2" class="pf w0 h0" data-page-no="2"><div class="pc pc2 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89621169/bg2.jpg"><div class="t m0 x1 h4 y11 ff5 fs3 fc0 sc0 ls0 ws0">缺点<span class="_ _2"> </span><span class="ff4">1</span>，对于我们想要的微弱的边缘，内置的<span class="_ _2"> </span><span class="ff4">canny<span class="_ _2"> </span></span>基本检测不出来，展示图像的例</div><div class="t m0 x1 h4 y12 ff5 fs3 fc0 sc0 ls0 ws0">子</div><div class="t m0 x1 h4 y13 ff5 fs3 fc0 sc0 ls0 ws0">缺点<span class="_ _2"> </span><span class="ff4">2</span>，内置的<span class="_ _2"> </span><span class="ff4">canny<span class="_ _2"> </span></span>大多数边缘也断断续续，展示图像的例子</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div><div id="pf3" class="pf w0 h0" data-page-no="3"><div class="pc pc3 w0 h0"><img class="bi x0 y0 w1 h1" alt="" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89621169/bg3.jpg"><div class="t m0 x1 h4 y14 ff5 fs3 fc0 sc0 ls0 ws0">缺点<span class="_ _2"> </span><span class="ff4">3</span>：擦除不方便，没法控制擦除大小</div><div class="t m0 x1 h4 y15 ff5 fs3 fc0 sc0 ls0 ws0">缺点<span class="_ _2"> </span><span class="ff4">4</span>：划线不方便，且断断续续</div></div><div class="pi" data-data='{"ctm":[1.611830,0.000000,0.000000,1.611830,0.000000,0.000000]}'></div></div>

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基于PCA人脸识别系统设计（matlab）
在此次研究中，为提高识别准确度和减少计算复杂度，成功开发了基于主要成分分析的人脸识别系统。采用PCA算法有效提取面部图像的关键特征，减少层次，特征提取，建立优化的特征空间，增强模型分类能力。在事前处理阶段，为了提高算法的稳定性，结合了灰度、直方图均衡化、杂声消除技术。实验结果表明，最近利用最近邻分类器在标准脸部数据集上进行了测试，该系统表现出了卓越的性能，证明了PCA在脸部识别领域的潜力。今后的研究将重点放在优化PCA算法，特别是PCA算法在处理真实场景时的适应性，如照明、表情变化和部分屏蔽。
人工智能
PCA人脸识别.zip 175.52KB
10 月前