May 26, 2020 —Sjoerd斯密特，技术顾问，欧洲钨manbet万博app
As more technology is folded into medical environments all over the world, Wolfram’s European branch has taken on work with the United Kingdom’s国家健康服务(NHS) in an effort to partially automate the process of cancer diagnosis. The task is to use machine learning to avoid checking thousands of similar-looking images of people’s insides by hand for signs of cancer.
May 19, 2020 —沙迪Ashnai，Manager of Sound & Vision, Algorithms R&D
12.1版of the Wolfram Language introduces the long-awaited视频宾语。该视频目的是完全（只）外的核心;它可以连接到一个广泛的视频容器的清单，几乎任何codec。最重要的是，它是捆绑在一起的完整的栈图片and音频处理，机器学习and神经网络，statisticsand可视化and many more capabilities. This already makes the Wolfram Language a powerful video computation platform, but there are still more features to explore.
We are excited to announceIntroduction to Image Processing，a free interactive course frommanbet万博app沃尔弗拉姆ü，which makes cutting-edge image processing simple with graphical and visual examples that demonstrate how image operations work. It includes 14 video lessons, each lasting 20 minutes or fewer, and 5 short quizzes, as well as a certificate for finishing all course materials. Topics range from how to control brightness and contrast or crop and resize images, to advanced topics including segmentation, image enhancement, feature detection and using machine learning to perform modern image processing—no machine learning knowledge necessary!
2019年12月23日 -乔恩·麦克龙，Director, Technical Communication & Strategy
对我们许多人来说,编程代表休闲蒂姆e just as much as work. Here at Wolfram, we have an incredibly creative group with a wide variety of hobbies, on the screen and off—including textile arts likecross-stitch。So when my colleague Jay suggested that I create a cross-stitch program using theWolfram Language我回答道：“接受挑战！”周杰伦一直在寻找一种简单的方法来产生从照片-或真跨缝图案的任何图像与对应于该颜色DMC线ID号。我们都知道，Wolfram语言的图像处理能力，将使这一件容易的事，但结合DMC线程目录似乎是一个有趣的挑战。manbet万博app与计算机和（虚拟）线程的武装，我开始对我的追求，创造完美的十字绣图案发生器。
May 2, 2019 —Tuseeta班纳吉，研究科学家，机器学习
If you haven’t used machine learning, deep learning and neural networks yourself, you’ve almost certainly heard of them. You may be familiar with their commercial use in self-driving cars, image recognition, automatic text completion, text translation and other complex data analysis, but you can also train your own neural nets to accomplish tasks like identifying objects in images, generating sequences of text or segmenting pixels of an image. With theWolfram Language，你可以开始使用机器学习和神经网络比你想象的要快。由于深学习和神经网络无处不在，让我们继续探索究竟它们是什么以及如何开始使用它们。
2018年1月12日 -Jesse Dohmann，Technical Documentation Writer, Document & Media Systems
并有人从朱诺任务的图像提供给公众，我想这可能是有趣的尝试我的手在与他们的一些图像处理。虽然我的背景是不是在图像处理中，Wolfram Languagehas some really nice tools that lessen the learning curve, so you can focus on what you want to do vs. how to do it.
Microscopes were invented almost four hundred years ago. But today, there’s a revolution in microscopy (as in so many other fields) associated with computation. We’ve been working hard to make theWolfram Language用于计算显微镜的这一新兴领域的权威平台。
它与得到某种-是否从光或X射线显微镜，透射电子显微镜（TEM），共聚焦激光扫描显微镜（CLSM）的图像的所有启动时，双光子激发或扫描电子显微镜（SEM），如以及更多。然后，您可以继续增强图像，改造对象并进行测量，探测，识别和分类。在上个月的Microscopy & Microanalysis conference，我们发现这条管线的各种例子，从一个蔡司显微镜和ToupTek数码相机。
February 23, 2017 —Michael Trott首席科学家，钨| Alpha的科学内涵manbet万博app
And How Many Animals, Animal Heads, Human Faces, Aliens and Ghosts in Their 2D Projections?
In my recent Wolfram Community post, “一个多少动物可以在随机图像找到？”我看着pareidoliaphenomenon from the viewpoints of pixel clusters in random (2D) black-and-white images. Here are some of the shapes I found, extracted, rotated, smoothed and colored from the connected black pixel clusters of a single 800×800 image of randomly chosen, uncorrelated black-and-white pixels.
January 31, 2017 —迈克尔金门，博客管理员，文档和媒体系统
If aliens actually visited Earth, world leaders would bring in a scientist to develop a process for understanding their language. So when director Denis Villeneuve began working on the science fiction movie到达他,一个nd his team turned to real-life computer scientists Stephen and Christopher Wolfram to bring authentic science to the big screen. Christopher specifically was tasked with analyzing and writing code for a fictional nonlinear visual language. On January 31, he demonstrated the development process he went through in a livecoding event you canwatch on YouTube。