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alexnadratupu's Projects

acf_gpu icon acf_gpu

GPU version of ACF pedestrian detection

adminmongo icon adminmongo

adminMongo is a Web based user interface (GUI) to handle all your MongoDB connections/databases needs.

anima-public icon anima-public

Open source software for medical image processing from the VISAGES team

awesomebump icon awesomebump

AwesomeBump is a free program written using Qt library designed to generate normal, height, specular or ambient occlusion textures from a single image. Since the image processing is done in 99% on GPU the program runs very fast and all the parameters can be changed in real time. AB was made to be a new alternative to known gimp plugin called Insane Bump.

brainstools icon brainstools

A suite of tools for medical image processing focused on brain analysis

cmt-cnn icon cmt-cnn

Learning Cross-Modal Deep Representations for Robust Pedestrian Detection

deepped icon deepped

Convolutional Neural Networks for Pedestrian Detection

dlib icon dlib

A toolkit for making real world machine learning and data analysis applications in C++

ecommerce icon ecommerce

Boho Glo is an e-commerce site that offers bohemian style clothes for purchase. The framework of this site can be used for multiple products or services. Technologies: Mongo, Mongoose, Node.js, Express, Ajax, Stripe, Elastic Search, Bootstrap.

hog_matlab icon hog_matlab

Matlab implementation of the HOG descriptor for pedestrian detection

imageq icon imageq

Qt based image processing application.

learning-image-processing icon learning-image-processing

C++ Image Processing Software developed in the QT Creator IDE and using DCMTK library for working with medical images

medicaltile icon medicaltile

A 3D/4D medical image visualization and processing tool.

mongo-express icon mongo-express

Web-based MongoDB admin interface, written with Node.js and express

object-tracking-blogpost icon object-tracking-blogpost

Use C++ with OpenCV and cvBlob to perform image processing and object tracking, using a webcam. Originally, built to test Raspberry Pi performance.

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