# convolutional neural networks

Published articles for convolutional neural networks.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Presenting Project Ergo: How to Build an Airplane Detector for Satellite Imagery With Deep Learning

DevFeed: [Presenting Project Ergo: How to Build an Airplane Detector for Satellite Imagery With Deep Learning](<https://devfeed.tech/articles/presenting-project-ergo-how-to-build-an-airplane-detector-for-satellite-imagery-with-deep-learning-41260.md>)

Original publisher: [Read original article](<https://www.evilsocket.net/2018/11/22/Presenting-project-Ergo-how-to-build-an-airplane-detector-for-satellite-imagery-with-Deep-Learning/>)

Author: Simone Margaritelli

Published: 2018-11-22T17:15:50Z

Content type: tutorial

Language: en

Sources: [evilsocket](<https://devfeed.tech/sources/evilsocket.md>)

Topics: [Keras](<https://devfeed.tech/topics/keras.md>), [Tensorflow](<https://devfeed.tech/topics/tensorflow.md>), [Framework](<https://devfeed.tech/topics/framework.md>), [Deep learning](<https://devfeed.tech/topics/deep-learning.md>), [Deep neural networks](<https://devfeed.tech/topics/deep-neural-networks.md>), [datasets](<https://devfeed.tech/topics/datasets.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Code](<https://devfeed.tech/topics/code.md>), [Development](<https://devfeed.tech/topics/development.md>), [Back end](<https://devfeed.tech/topics/backend.md>), [Python](<https://devfeed.tech/topics/python.md>), [Shell](<https://devfeed.tech/topics/shell.md>)

Tags: [cnn](<https://devfeed.tech/tags/cnn.md>), [code](<https://devfeed.tech/tags/code.md>), [computer-vision](<https://devfeed.tech/tags/computer-vision.md>), [convolutional-neural-networks](<https://devfeed.tech/tags/convolutional-neural-networks.md>), [cpu](<https://devfeed.tech/tags/cpu.md>), [cuda](<https://devfeed.tech/tags/cuda.md>), [cudnn](<https://devfeed.tech/tags/cudnn.md>), [cybersecurity](<https://devfeed.tech/tags/cybersecurity.md>), [deep-learning](<https://devfeed.tech/tags/deep-learning.md>), [deep-neural-networks](<https://devfeed.tech/tags/deep-neural-networks.md>), [dnn](<https://devfeed.tech/tags/dnn.md>), [ergo](<https://devfeed.tech/tags/ergo.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [image-classification](<https://devfeed.tech/tags/image-classification.md>), [keras](<https://devfeed.tech/tags/keras.md>), [machine-learning](<https://devfeed.tech/tags/machine-learning.md>), [neural-networks](<https://devfeed.tech/tags/neural-networks.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [planes](<https://devfeed.tech/tags/planes.md>), [planes-detector](<https://devfeed.tech/tags/planes-detector.md>), [planesnet](<https://devfeed.tech/tags/planesnet.md>), [project-release](<https://devfeed.tech/tags/project-release.md>), [python](<https://devfeed.tech/tags/python.md>), [shell](<https://devfeed.tech/tags/shell.md>), [tensorflow](<https://devfeed.tech/tags/tensorflow.md>), [tf](<https://devfeed.tech/tags/tf.md>), [train](<https://devfeed.tech/tags/train.md>), [training](<https://devfeed.tech/tags/training.md>), [tutorial](<https://devfeed.tech/tags/tutorial.md>)

### AI overview

The article introduces Project Ergo, an open-source framework and manager for Keras-based machine-learning projects. It demonstrates prototyping, training, and testing a convolutional neural network with the PlanesNet dataset to build an airplane detector for satellite imagery, including CPU and GPU setup considerations.

### Source excerpt

It's been a while that i've been quite intensively playing with Deep Learning both for work related research and personal projects. More specifically, I've been using the Keras framework on top of a TensorFlow backend for all sorts of stuff. From big and complex projects for malware detection, to smaller and simpler experiments about ideas i just wanted to quickly implement and test - it didn't really matter the scope of the project, I always found myself struggling with the same issues: code reuse over tens of crap python and shell scripts, datasets and models that are spread all over my dev and prod servers, no real standard for versioning them, no order, no structure. So a few days ago I started writing what it was initially meant to be just a simple wrapper for the main commands of my training pipelines but quickly became a full-fledged framework and manager for all my Keras based projects. Today I'm pleased to open source and present project Ergo by showcasing an example use-case: we'll prototype, train and test a Convolutional Neural Network on top of the PlanesNet raw dataset in order to build an airplane detector for satellite imagery.

## waifu2x super resolution image resizer

DevFeed: [waifu2x super resolution image resizer](<https://devfeed.tech/articles/waifu2x-super-resolution-image-resizer-37358.md>)

Original publisher: [Read original article](<https://muffinman.io/blog/super-resolution-image-resizer/>)

Author: Stanko

Published: 2017-06-26T00:00:00Z

Content type: opinion

Language: en

Sources: [Stanko Tadić](<https://devfeed.tech/sources/stanko-tadic.md>)

Topics: [Deep neural networks](<https://devfeed.tech/topics/deep-neural-networks.md>), [Website](<https://devfeed.tech/topics/website.md>), [Code](<https://devfeed.tech/topics/code.md>), [GitHub](<https://devfeed.tech/topics/github.md>)

Tags: [convolutional-neural-networks](<https://devfeed.tech/tags/convolutional-neural-networks.md>), [github](<https://devfeed.tech/tags/github.md>), [image](<https://devfeed.tech/tags/image.md>), [jpeg](<https://devfeed.tech/tags/jpeg.md>), [neural-networks](<https://devfeed.tech/tags/neural-networks.md>), [opensource](<https://devfeed.tech/tags/opensource.md>), [scaling](<https://devfeed.tech/tags/scaling.md>), [super-resolution](<https://devfeed.tech/tags/super-resolution.md>)

### AI overview

A personal review of waifu2x, a free open-source website and project that uses deep convolutional neural networks to enlarge images. The article notes that it supports up to 2x scaling and can produce a 500x500 PNG from a 250x250 JPEG.

### Source excerpt

I use the same wallpaper for a long time now. But with high resolution displays, wallpaper started to look blurry and noisy, so I stopped using it. But recently, my girlfriend reminded me of this great website which super-scales images using magic. Ok, not magic, but it uses "Deep Convolutional Neural Networks", which is pretty much the same thing. Results are amazing, try it yourself. The best thing, website is free to use and project is opensource. Code is available on GitHub. It supports max scaling of 2x, so if you need more you'll need to process image multiple times. Or you can dig in the code and add option for arbitrary scaling. 1 This is the resized image using waifu2x. Example # Original, 250x250px jpeg 2 Result, 500x500px png If you ask me, results are really impressive, kudos to nagadomi!