基于MATLAB的人体目标检测主要调用MATLAB自带的yolov3对人体检测

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ZIP 基于的人体目标检测主要调用自带.zip 大约有13个文件
  1. 1.jpg 309.52KB
  2. 2.jpg 136.5KB
  3. 3.jpg 132.4KB
  4. 下的人体目标检测的实践之旅在数字化和智能化的时代人.txt 2.11KB
  5. 基于的人体目标检测主.html 4.69KB
  6. 基于的人体目标检测利用算法实现精确识.txt 2.64KB
  7. 基于的人体目标检测技术分析一引言随着人工智能技.txt 1.64KB
  8. 基于的人体目标检测技术分析随着人工智能技术的快.txt 2.13KB
  9. 基于的人体目标检测技术研究与应用探讨摘要本文主要.txt 2.32KB
  10. 基于的人体目标检测技术解析与实现一引.doc 2.57KB
  11. 基于的人体目标检测深入探索与实现一引.doc 2.44KB
  12. 基于的人体目标检测的应.html 10.02KB
  13. 基于的人体目标检测随着计算机视觉技术.txt 2.56KB

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基于MATLAB的人体目标检测 主要调用MATLAB自带的yolov3对人体检测
<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/90240175/2/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/90240175/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">基于<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">YOLOv3<span class="_ _1"> </span></span>人体目标检测技术解析与实现</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff3">、</span>引言</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">随着计算机视觉技术的不断发展<span class="ff4">，</span>目标检测已经成为图像处理领域的重要研究方向<span class="ff3">。</span>人体目标检测作</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">为其中的一种<span class="ff4">，</span>其应用广泛<span class="ff4">，</span>例如在安全监控<span class="ff3">、</span>人机交互<span class="ff3">、</span>智能交通等领域都有着重要的应用<span class="ff3">。</span>本文</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">将以<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>平台为基础<span class="ff4">，</span>介绍如何使用<span class="_ _0"> </span><span class="ff2">YOLOv3<span class="_ _1"> </span></span>算法进行人体目标检测<span class="ff4">，</span>旨在帮助读者了解并掌握</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">这一技术<span class="ff3">。</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff3">、<span class="ff2">YOLOv3<span class="_ _1"> </span></span></span>算法概述</div><div class="t m0 x1 h2 y8 ff2 fs0 fc0 sc0 ls0 ws0">YOLO<span class="ff4">（</span>You Only Look Once<span class="ff4">）<span class="ff1">是一种实时目标检测算法</span>，<span class="ff1">以其高速度<span class="ff3">、</span>高准确率的特点在目标检</span></span></div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">测领域受到广泛关注<span class="ff3">。<span class="ff2">YOLOv3<span class="_ _1"> </span></span></span>作为<span class="_ _0"> </span><span class="ff2">YOLO<span class="_ _1"> </span></span>系列算法的最新版本<span class="ff4">，</span>进一步提高了检测的准确率和速度</div><div class="t m0 x1 h2 ya ff3 fs0 fc0 sc0 ls0 ws0">。<span class="ff1">该算法通过单次前向传播即可预测多个目标的位置和类别<span class="ff4">，</span>具有强大的实时性和准确性</span>。</div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">三<span class="ff3">、<span class="ff2">MATLAB<span class="_ _1"> </span></span></span>环境准备</div><div class="t m0 x1 h2 yc ff2 fs0 fc0 sc0 ls0 ws0">MATLAB<span class="_ _1"> </span><span class="ff1">是一款功能强大的数学软件<span class="ff4">，</span>提供了丰富的图像处理库和工具<span class="ff3">。</span>在进行<span class="_ _0"> </span></span>YOLOv3<span class="_ _1"> </span><span class="ff1">人体目标检</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">测之前<span class="ff4">，</span>我们需要确保<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>环境已经安装并配置好<span class="ff4">，</span>并且已经安装了<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff2">Image </span></div><div class="t m0 x1 h2 ye ff2 fs0 fc0 sc0 ls0 ws0">Processing Toolbox<span class="_ _1"> </span><span class="ff1">和<span class="_ _0"> </span></span>Computer Vision Toolbox<span class="ff3">。</span></div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">四<span class="ff3">、<span class="ff2">YOLOv3<span class="_ _1"> </span></span></span>模型训练</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">在进行<span class="_ _0"> </span><span class="ff2">YOLOv3<span class="_ _1"> </span></span>模型训练之前<span class="ff4">，</span>我们需要准备人体目标的标注数据<span class="ff3">。</span>标注数据包括图像和对应的目标</div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">位置信息<span class="ff3">。</span>通常<span class="ff4">，</span>这些数据以<span class="_ _0"> </span><span class="ff2">XML<span class="_ _1"> </span></span>或<span class="_ _0"> </span><span class="ff2">TXT<span class="_ _1"> </span></span>格式存储<span class="ff3">。</span>然后<span class="ff4">，</span>我们可以使用<span class="_ _0"> </span><span class="ff2">MATLAB<span class="_ _1"> </span></span>中的<span class="_ _0"> </span><span class="ff2">YOLOv3<span class="_ _1"> </span></span>预</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">训练模型进行微调<span class="ff4">，</span>以适应我们的数据集<span class="ff3">。</span>需要注意的是<span class="ff4">，</span>模型训练需要消耗大量的计算资源<span class="ff4">，</span>包括</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">时间和硬件资源<span class="ff4">，</span>因此建议在合适的硬件条件下进行<span class="ff3">。</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>
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