Search Results for "learning"
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Showing 11 open source projects for "learning"
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Image Fusion
Deep Learning-based Image Fusion: A Survey
This repository is a survey / code collection centered on deep learning–based image fusion (e.g. fusing infrared + visible light images, multi-modal fusion) methods. It catalogs many fusion algorithms (e.g. DenseFuse, FusionGAN, NestFuse, etc.), links to code implementations, and describes evaluation metrics. The repository includes a “General Evaluation Metric” subfolder containing objective fusion metrics. -
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Armadillo
fast C++ library for linear algebra & scientific computing
* Fast C++ library for linear algebra (matrix maths) and scientific computing * Easy to use functions and syntax, deliberately similar to Matlab / Octave * Uses template meta-programming techniques to increase efficiency * Provides user-friendly wrappers for OpenBLAS, Intel MKL, LAPACK, ATLAS, ARPACK, SuperLU and FFTW libraries * Useful for machine learning, pattern recognition, signal processing, bioinformatics, statistics, finance, etc. * Downloads: http://arma.sourceforge.net/download.html * Documentation: http://arma.sourceforge.net/docs.html * Bug reports: http://arma.sourceforge.net/faq.html * Git repo: https://gitlab.com/conradsnicta/armadillo-code -
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MTCNN Face Detection Alignment
Joint Face Detection and Alignment
...The algorithm uses a cascade of three convolutional networks (P-Net, R-Net, O-Net) to jointly detect faces (bounding boxes) and align facial landmarks in a coarse-to-fine manner, leveraging multi-task learning. Non-maximum suppression and bounding box regression at each stage. The repository includes Caffe / MATLAB code, support scripts, and instructions for dependencies. Non-maximum suppression and bounding box regression at each stage. Online hard sample mining to improve training robustness. -
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DnCNN
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN
This repository implements DnCNN (“Deep CNN Denoiser”) from the paper “Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising”. DnCNN is a feedforward convolutional neural network that learns to predict the residual noise (i.e. noise map) from a noisy input image, which is then subtracted to yield a clean image. This formulation allows efficient denoising, supports blind Gaussian noise (i.e. unknown noise levels), and can be extended to related tasks like image super-resolution or JPEG deblocking in some variants. ... -
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OpenFace
A state-of-the-art facial behavior analysis toolkit
OpenFace is an advanced facial behavior analysis toolkit intended for computer vision and machine learning researchers, those in the affective computing community, and those who are simply interested in creating interactive applications based on facial behavior analysis. The OpenFace toolkit is capable of performing several complex facial analysis tasks, including facial landmark detection, eye-gaze estimation, head pose estimation and facial action unit recognition. -
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Mexopencv
Collection and a development kit of matlab mex functions for OpenCV
mexopencv is a collection of MEX functions that provide MATLAB bindings for OpenCV, the popular computer vision library. It enables MATLAB users to access nearly the full range of OpenCV’s C++ API directly from MATLAB, combining the ease of MATLAB scripting with the performance of OpenCV. -
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Netvlad
NetVLAD: CNN architecture for weakly supervised place recognition
NetVLAD is a deep learning-based image descriptor framework developed by Relja Arandjelović for place recognition and image retrieval. It extends standard CNNs with a trainable VLAD (Vector of Locally Aggregated Descriptors) layer to create compact, robust global descriptors from image features. This implementation includes training code and pretrained models using the Pittsburgh and Tokyo datasets. -
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OpenTLD
OpenTLD is an open source library for real-time 2D tracking
OpenTLD is an open source implementation of the TLD (Tracking-Learning-Detection) framework, designed for real-time 2D tracking of a single object in video sequences. Because it fuses tracking and detection, TLD can recover from occlusions, drift, or failures by using its detection mechanism to reacquire the object. In terms of usage, one typically initializes the tracker by providing a bounding box on the first frame, then calls a function like run_TLD to process a video and obtain bounding boxes over time. ... -
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Rcnn
R-CNN: Regions with Convolutional Neural Network Features
This repository contains the original MATLAB implementation of R-CNN (Regions with Convolutional Neural Networks), a pioneering deep learning-based object detection framework. Developed by Ross Girshick, R-CNN combines region proposals with convolutional neural networks to detect objects in images. It was one of the first approaches to significantly improve performance on object detection benchmarks like PASCAL VOC. -
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Overhead Imagery Research Data Set (OIRDS) - an annotated data library & tools to aid in the development of computer vision algorithms
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