Network configuration and management for Nerves devices

Connect to wired and wireless networks on Nerves platforms.

**Deprecated** Connect to WiFi networks on Nerves platforms

**Deprecated** Ethernet management for Nerves

Discover, setup, and get stats on network interfaces

Networked, discoverable, updatable devices for Nerves

Bolt ⚡ - Network monitor (Nerves) and UI (Phoenix/Elixir) in poncho configuration

Learn how to use the Nerves embedded framework to build incredibly efficient & fault-tollerant network devices (IoT)

For Nerves projects with networking. Gives VintageNet a kick if there's no internet connectivity, falling back on a reboot after 3 kicks.

Lower back pain is a major cause of morbidity in the developed world, affecting 40% of people at some point in their lives. Back pain can be caused by a variety of problems with any parts of the complex, interconnected network of spinal muscles, nerves, bones, discs, or tendons in the lumbar spine.

Using Convolutional Neural Networks to automatically segment nerves from ultrasound images

Nerves example project showing how to use the Hologram Nova for cellular network connection

Nerves device to collect data from a NMEA2000 network, or LoRa, and upload to nautic_net_web

Human retina contains vast information on the presence of diseases in a human body. Any abnormalities in these tissues can help in the diagnosis of ophthalmic and cardiovascular diseases. This study process requires extracting a segmented image of the retinal vessel from the retinal image, which makes the doctors work easier. This paper presents an AI model to extract the segmentation from the retinal image. The model is based on General Adversarial Network(GAN) trained on perceptual loss. GAN models are known to generate data that are much realistic based on the input information. Perceptual loss helps the model recognise the differences in the features of the extracted image and the expected manually segmented images. Perceptual loss will help train the model to provide better accuracy. The model consists of a generator based on U-Net model, 3 discriminators to which work on different receptive fields. The perceptual loss is calculated based on the features extracted by a pre-trained LeNet Model. The model is trained on 2 datasets, namely Digital Retinal Images for Vessel Extraction(DRIVE) and Structured Analysis of Retina(STARE). The use of multiple discriminators and perceptual loss to judge the generation of the image helps the model to segment even the dimmest nerves. The performance of the model is better compared to the existing U-Net model or the GAN model.

Nerves Phoenix 1.3 template with wireless network and sqlite db

Ultrasound nerve segmentation using deep learning refers to the process of training neural network models to identify and outline nerves in ultrasound images. These models learn from labeled data to accurately locate nerves, aiding medical professionals in diagnostics and treatment planning.

Modified Nerves System for the RPi3 with additions for Hologram Nova cellular network connection

Bihemispheric neuromorphic neural network/Inspired by the nerves of the human brain/Separate, coordinated and simultaneous processing and simulation of the corpus callosum of the brain in the network and pre-processing layer, any copying is prohibited. PCT/IR2025/050026

Wi-Every (Wi-Fi Everywhere) — is a free mobile App for Android phones which covers the area of Kharkiv city(Ukraine). The application indicates all avaliable both open and coded access to Wi-fi, creating one large network While moving around the city — Wi-Every defines the nearest wi-fi hotspot with the best signal strengh and automatically connects your device to the best network in every location. Wi-fi signal-in-motion may vary with a strength. Wi-Every is a great nerves-saver application which will keep your mood up. The users are able to add new open and coded wi-fi hotspots to the App, enhancing the wi-fi coverage network in Kharkiv city.

Glaucoma is dangerous eye disease because it causes permanent blindness by damaging the optic nerves. The data shows that it is one of the leading causes of blindness and second most eye disease proceeding by cataract so, Diagnosis of this disease in early stage is essential to avoid partial or full loss of eye vision.In this work, Glaucoma will be detected using image processing methods on eye fundus images using SRGAN enhancement with UNET image segmentation and classified using a convolution neural network. NOTE: To access the dataset unzip the file name called "main.zip" that zip file contains the dataset.

Utilize nerves_networking library to start network adapter for nerves build of LinkBlox application

an example of nerves distributed clustering on a local wifi network.

Elixir nerves network hello world

AV sensor network with Elixir/Nerves

hello_network using nerves_system_qemu_arm

Nerves project for an alarm clock that plays network streams.

Hopfield Network solution for the course - Introduction to Neural Networks and Models of the Nerves System

A structure in the form of a network, especially of nerves, blood vessels, or lymphatics.

A structure in the form of a network, especially of nerves, blood vessels, or lymphatics.

Hodgkin Huxley Model solution for the course - Introduction to Neural Networks and Models of the Nerves System