GitHub – yggdrasil-network/yggdrasil-go: An experiment in scalable routing as an encrypted IPv6 overlay network

Yggdrasil is an early-stage implementation of a fully end-to-end encrypted IPv6 network. It is lightweight, self-arranging, supported on multiple platforms and allows pretty much any IPv6-capable application to communicate securely with other Yggdrasil nodes. Yggdrasil does not require you to have IPv6 Internet connectivity – it also works over IPv4. Source: GitHub – yggdrasil-network/yggdrasil-go: An […]

Ask HN: Why can’t I learn anymore? | Hacker News

The key to not having to deal with this problem anymore, for me, was starting to proactively switch things around to break the routine of consecutive work-weeks. One of my tricks was to do some kind of mini-vacation every 6-8 weeks, go somewhere new, leave work behind for 3-4 days. Even smaller things like regular […]

GitHub – ORB-HD/deface: Video anonymization by face detection

deface is a simple command-line tool for automatic anonymization of faces in videos or photos. It works by first detecting all human faces in each video frame and then applying an anonymization filter (blurring or black boxes) on each detected face region. All audio tracks are discarded as well. Source: GitHub – ORB-HD/deface: Video anonymization […]

How to resize ext4 Linux Partitions?

Back up data, make VM snapshots Prepare a Ubuntu LiveCD Boot from it Run GParted, and resize all the disks from there Remember to run fsck, or use GParted “check” feature

Deep learning examples on Raspberry 32/64 OS – Q-engineering

The overview speaks for itself. The highest frame rate measured comes from a Raspberry 64-bit OS overclocked to 1950 MHz. The lowest is the standard 32-bit Raspbian at 1500 MHz. Frame rates are only based on model run time (interpreter->Invoke()). Grabbing and preprocessing of an image are not taken into account, nor plotting output boxes […]

Deep learning with Raspberry Pi and alternatives in 2022 – Q-engineering

This page assists you to build your deep learning modal on a Raspberry Pi or an alternative like Google Coral or Jetson Nano. For more general information about deep learning and its limitations, please see deep learning. This page deals more with the general principles, so you have a good idea of how it works […]

Article: From MobileNet to EfficientNet

In this article, I’m going to walk through the architectural implementations that led from the first MobileNet architecture to the state of the art EfficientNet architecture, with a bunch of improvements in between. The MobileNet architecture was aimed at reducing the computational requirements for large neural networks without a large drop in performance on the […]

Review: SqueezeNet (Image Classification) | by Sik-Ho Tsang | Towards Data Science

Adding the simple bypass connections yielded an increase of 2.9 percentage-points in top-1 accuracy and 2.2 percentage-points in top-5 accuracy without increasing model size. Source: Review: SqueezeNet (Image Classification) | by Sik-Ho Tsang | Towards Data Science Scroll to the bottom of the page to see reviews of Neural Networks.