This means that almost 2 million newbies without any actual trading experience and lacking any specialized software for trading/position analysis have entered the market.
Manual lung segmentation takes about 10 minutes and it requires a certain skill to get the same high-quality result as with automatic segmentation. Automatic segmentation takes about 15 seconds.
I assumed that without a neural network it would be possible to get an accuracy of no more than 70%. I also assumed, that morphological operations are only the preparation of an image for more complex algorithms. But as a result of processing of those, although few, 40 samples of tomographic data on hand, the algorithm segmented the lungs without errors. Moreover, after testing in the first five cases, the algorithm didn’t change significantly and correctly worked on the other 35 studies without changing the settings.
Also, neural networks have a disadvantage — for their training we need hundreds of training samples of lungs, which need to be marked up manually.
We used to think of Telegram as a reliable and secure transmission medium for messages of any sort. But under the hood, it has a rather common combination of a- and symmetric encryptions. Where's fun in that? And anyway, why would anyone trust their messages to the third-party?
TL;DR — inventing a private covert channel over users blocking each other.
In this article I will explain a texture splatting algorithm which allows you to create more natural terrain. This algorithm may be used in shaders of 3D games as well as in 2D games.
The original post has been updated based on community input in order to remove confusion.
Final version of the whitepaper is available here:
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Our project implements a real-time edge detection system based on capturing image frames from an OV7670 camera and streaming them to a VGA monitor after applying a grayscale filter and Sobel operator. Our design is built on a Cyclone IV FPGA board which enables us to optimize the performance using the powerful features of the low-level hardware and parallel computations which is important to meet the requirements of the real-time system.
We used ZEOWAA FPGA development board which is based on Cyclone IV (EP4CE6E22C8N). Also, we used Quartus Prime Lite Edition as a development environment and Verilog HDL as a programming language. In addition, we used the built-in VGA interface to drive the VGA monitor, and GPIO (General Pins for Input and Output) to connect the external hardware with our board.