Jurnal Singkat

  https://webcapp.ccsu.edu/?news=1767&data   CCSU NEWS RELEASE WORLD’S MOST LITERATE NATIONS RANKED     For Release: March 9, 2016 NEW BRITAIN, CT:  The World’s Most Literate Nations (WMLN) study, the first to analyze large-scale trends in literate behavior and literacy in more than 60 countries, finds the Nordic countries (Finland, Norway, Iceland, Denmark, and Sweden,) are among the five most literate nations in the world, while the U.S. and Canada rank 7 th and 11 th respectively. The study, conducted by John W. Miller, president of Central Connecticut State University in New Britain, CT., is used as a lens to view literate behaviors and their supporting resources -- five categories such as size and number of libraries and newspaper readership. “The power of literacy and the value of being part of a literate world is often taken for granted,” observes Miller. Much of his academic work during the past 40 years has been devoted to literacy i...

  https://pidtuner.com/  Forum: https://forum.pidtuner.com/ Github: https://github.com/pidtuner/pidtuner.github.io Video: https://www.youtube.com/channel/UCkRD7FztiFOdX50BUsOkcSQ Why Tuning a PID controller can be easily done using a systematic procedure. We just put it in a web application. No more trial and error. How Use the step response data from your system and follow the wizard step-by-step. On each step you are free to make decisions to improve your tuning, but the defaults will work just fine.    Features Copy-paste data import Data validation and visualization Multi-model data fit Auto-tuned PID gains Interactive closed-loop simulations            

  https://analyticsindiamag.com/top-dataset-annotation-tools-for-computer-vision-tasks/ Google Vision API https://cloud.google.com/docs/tutorials#vision Intel CVAT https://github.com/openvinotoolkit/cvat IBM Cloud Annotation Tool https://cloud.annotations.ai/docs Google Fluid Annotation Scale: Video Annotation

  https://ai.googleblog.com/2018/10/fluid-annotation-exploratory-machine.html   Fluid Annotation: An Exploratory Machine Learning–Powered Interface for Faster Image Annotation    The performance of modern deep learning–based computer vision models, such as those implemented by the TensorFlow Object Detection API , depends on the availability of increasingly large, labeled training datasets, such as Open Images . However, obtaining high-quality training data is quickly becoming a major bottleneck in computer vision. This is especially the case for pixel-wise prediction tasks such as semantic segmentation , used in applications such as autonomous driving, robotics, and image search. Indeed, traditional manual labeling tools require an annotator to carefully click on the boundaries to outline each object in the image, which is tedious: labeling a single image in the COCO + Stuff dataset takes 19 minutes, while labeling the whole dataset would take over 5...

  https://github.com/openvinotoolkit/cvat CVAT is free, online, interactive video and image annotation tool for computer vision. It is being used by our team to annotate million of objects with different properties. Many UI and UX decisions are based on feedbacks from professional data annotation team. Try it online cvat.org .    

  https://timdaub.github.io/2020/02/19/wasm-synth/   Introduction Ever since I started taking piano lessons two years ago, I was curious to take a look into a vastly different field from cryptocurrencies and blockchain. That field being digital audio engineering. So when some of my freelance projects ended in November 2019, I decided to allocate my next three months towards building an audio product. I quickly discovered what I wanted to build: A synthesizer. In C++! I had just watched some talks on WebAssembly, and was very curious to learn a new language too! In hindsight, the personal challenge, however, was to understand the data structures and math that go into generating audio. That's the story of how I rediscovered the beauty of mathematics through building a synthesizer with C++ and WebAssembly. Theory I had never done anything in the field of music technology - I had to start at zero practically. It meant I had to look at the physical, mathematical, an...

  https://ai.facebook.com/blog/wav2vec-unsupervised-speech-recognition-without-supervision/   What the research is: Whether it’s giving directions, answering questions, or carrying out requests, speech recognition makes life easier in countless ways. But today the technology is available for only a small fraction of the thousands of languages spoken around the globe. This is because high-quality systems need to be trained with large amounts of transcribed speech audio. This data simply isn’t available for every language, dialect, and speaking style. Transcribed recordings of English-language novels, for example, will do little to help machines learn to understand a Basque speaker ordering food off a menu or a Tagalog speaker giving a business presentation. This is why we developed wav2vec Unsupervised (wav2vec-U), a way to build speech recognition systems that require no transcribed data at all. It rivals the performance of the best supervised models from only a f...