字幕整理:Fei-Fei Li: How computer understand the world?

整理内容来自:Fei-Fei Li: How computer understand the world?

闲来无事,听了李菲菲博士(女神)在TED上的精彩报告。科普性很好,语言很流畅,可以作为计算机视觉方向英语口语练习的好材料,就把字幕整理了下来,以备学习方便

Let me show you something.

(Video) Girl: Okay, that's a cat sitting in a bed. 
                      The boy is petting the elephant.
                       Those are people that are going on an airplane. That's a big airplane.
Fei-Feo Li: That's a three-year-old child describing what she sees in a series of photos. She might still have a lot to learn about this world, but she's already an expert at one very important task: to make sense of what she sees.
      Our society is more technologically advanced than ever. We send people to the moon, we make phones that talk to us or customize radio stations that can play only music we like. Yet, our most advanced machines and computers still struggle at this task. So I'm here today to give you a progess report on the latest advances in our research in computer vision, one of the most frontier and potentially revolutionary techniques in computer science. 
      Yes, we have prototyped cars that can drive by themselves, but without smart vision, they cannot tell the difference between a crumpled paper bag on the ground, which can be run over, and a rock that size, which should be avoided. We have made fabulous megapixel cameras, but we have not delivered sight to  the blind. Drones  can fly over massive land, but don't have enough vision technology to help us to track the change of the rainforests. Security cameras are everywhere, but they do no alter us when a child is drowing in a swimming pool. Photos and videos are becoming an integral part of global life. They are being generated at a pace that's far beyond what any human or teams of humans, could hope ot view, and you and I are contributing to that at thsi TED. 
      Yet, our most advanced software is still struggling at understanding and managing this enormous content. So in other words, collectively as a society, we're very blind, because our smartest machines are still blind. "Why is this so hard?" you may ask. Camera can take pictures like this one by converting lights into a two-dimensional array of numbers known as pixe
【SCI级别】多策略改进鲸鱼优化算法(HHWOA)和鲸鱼优化算法(WOA)在CEC2017测试集函数F1-F30寻优对比内容概要:本文档主要介绍了一项关于多策略改进鲸鱼优化算法(HHWOA)与标准鲸鱼优化算法(WOA)在CEC2017测试集函数F1-F30上进行寻优性能对比的研究,属于智能优化算法领域的高水平科研工作。文中通过Matlab代码实现算法仿真,重点展示了HHWOA在收敛速度、寻优精度和稳定性方面的优势,体现了多策略改进的有效性。该研究适用于复杂优化问题求解,尤其在工程优化、参数辨识、机器学习超参数调优等领域具有应用潜力。; 适合人群:具备一定算法基础和Matlab编程能力的研究生、科研人员及从事智能优化算法开发与应用的工程技术人员,尤其适合致力于SCI论文写作与算法创新的研究者。; 使用场景及目标:①用于理解鲸鱼优化算法的基本原理及多策略改进思路(如种群初始化、非线性收敛因子、精英反向学习等);②为智能优化算法的性能测试与对比实验提供CEC2017标准测试平台的实现参考;③支撑学术研究中的算法创新与论文复现工作。; 阅读建议:建议结合提供的Matlab代码进行实践操作,重点关注HHWOA的改进策略模块与WOA的差异,通过重复实验验证算法性能,并可将其思想迁移至其他优化算法的改进中,提升科研创新能力。
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