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MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on...
ExDARK dataset is the largest collection of low-light images
The Exclusively Dark (ExDARK) dataset is one of the largest curated collections of real-world low-light images designed to support research in computer vision tasks under challenging lighting conditions. It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification...
...Supports search, autocompletion, launching scripts, interactive console, debug and integrated plotting on Octave versions 3.2.x, 3.4.x and 3.6.x.
The current goal is to make it running out-of-box on multiple platforms. Currently only Linux and Windows are supported.
Mac support is possible. The project needs a maintainer for Mac version, since I don't have Mac to build Octclipse and test it on this platform.
Also, it is worth to support Eclipse 4.0 Juno with DLTK 4.