BEGIN:VCALENDAR VERSION:2.0 PRODID:-//PYVOBJECT//NONSGML Version 1//EN BEGIN:VTIMEZONE TZID:Asia/Shanghai BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:CST TZOFFSETFROM:+0800 TZOFFSETTO:+0800 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:20260709T073308Z - 33258@iZuf69e0i0z4ibdboqb33jZ DTSTART;TZID=Asia/Shanghai:20230807T020000 DTEND;TZID=Asia/Shanghai:20230807T040000 CREATED:20260709T073308Z DESCRIPTION:How Machines See: Convolution al neural network 机器图像识别:卷积神经网络\nIn our lates t of clubs where we geek out hard in our quest to better understand machin es to make sure they don't control us too soon\, we're going to talk about how they see. Facial recognition is very much here\, let's learn about an d discuss how it works._x000D_ _x000D_ So\, how do machines see? How does it compare to how we see? How do they actually recognize images? And what in the matrix is the "convolutional neural network"? _x000D_ _x000D_ In th e past\, image recognition is an area in which machines constantly failed. .. Until we leveraged neural networks to do the job and\, once again\, rev olutionize technology. In 2012\, AlexNet achieved so much attention that i t brought on the deep learning era which is still thriving loudly today. L et's do some deep learning of our own and let's have an intelligent and fa scinating discussion! Let's look into the convolutional idea and the mecha nics of how machines see._x000D_ _x000D_ 在我们最近的活动中，我 们努力探索更好地理解机器，以确保它们不会过早地控 制我们，我们将讨论它们是如何看见周围的。面部识别 在这里非常重要，让我们来学习和讨论它是如何工作的 。_x000D_ _x000D_ 那么，机器是怎么看东西的呢?它和我们看 到的相比如何?它们是如何识别图像的?矩阵中的什么是“ 卷积神经网络”?_x000D_ _x000D_ 在过去，机器图像识别是一 个经常失败的领域。直到我们利用神经网络来完成这项 工作，再一次彻底改变技术。2012年，AlexNet获得了如此多 的关注，它带来了深度学习时代，今天仍然在蓬勃发展 。让我们自己做一些深入的学习，让我们来一个聪明而 有趣的讨论!让我们来看看卷积的思想和机器图像识别的 机制。 DTSTAMP:20260709T073308Z LOCATION:China\,\, Shanghai SUMMARY:How Machines See: Convolutional neural network 机器图像识别:卷积神经网络 END:VEVENT END:VCALENDAR