Falcon Contributors | Logo based on a Vic,-3.1.2008.jpg>photograph by John O'Neill. Created using Sphinx 1.4.8. index modules | next | Falcon Contributors | Logo based on a Vic,-3.1.2008.jpg>photograph by John O'Neill. Created using Sphinx 1.4.8. index modules | next | Falcon Contributors | Logo based on a Vic,-3.1.2008.jpg>photograph by John O'Neill. Created using Sphinx 1.4.8. index modules | next |

usage of functions towards the end. https://images.rawpixel.com/image_800/cHJpdmF0ZS9sci9pbWFnZXMvd2Vic2l0ZS8yMDIyLTA1L2pvYjcxMC0wNTMuanBn.jpg 9Functions A familiar term -- perhaps from your math class

任务一直是学术界和产业界共同关注的热点。 自然场景人脸检测在美团业务中也有着广泛的应用需求，为了应对自然场景应用本 身的技术挑战，同时满足业务的性能需求，美团视觉智能中心（Vision Intelligence Center，VIC）从底层算法模型和系统架构两个方面进行了改进，开发了高精度人脸 检测模型 VICFace。而且 VICFace 在国际知名的公开测评集 WIDER FACE 上达 到了行业主流水平。 图 1 自然场景人脸检测样本示例 是一种检测性能和速度平衡的算法，也是当前人脸检测算法优化的主流方向。 三、 优化思路和业务应用 在自然场景应用中，为了同时满足精度需求以及达到实用的目标，美团视觉智能中心 （Vision Intelligence Center，VIC）采用了主流的 Anchor-Based 单阶段人脸检测 算法 < 291 方案，同时在数据增强和采样策略、模型结构设计和损失函数等三方面分别进行了优 化，开发了高精度人脸检测模型 VICFace，以下是相关技术细节的介绍。

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@pkmooreanaconda • @tl-hbk made their first contribution in https://github.com/conda/conda/pull/12604 • @vic-ma made their first contribution in https://github.com/conda/conda/pull/12579 • @pre-commit-ci[bot]

method on the names array: 1 var names = ["Mohsen", "Hilary", "Justyn", "Amy", "Rich", "Graham", "Vic"] 2 var copiedNames = names.copy() You can prove that the names array has been copied by changing

Release 4.0.0 Thomas Grainger, Tomas Machalek, Tobias Schottdorf, Tocho Tochev, Valentyn Klindukh, Vic Kumar, Vladimir Bol- shakov, Vladimir Gorbunov, Wayne Chang, Wieland Hoffmann, Wido den Hollander,