OpenCV: Real Time pose estimation of a textured object
Nowadays, augmented reality is one of the top research topic in computer vision and robotics fields. The most elemental problem in augmented reality is the estimation of the camera pose respect of an object in the case of computer vision area to perform subsequent 3D rendering or, in robotics, to obtain an object pose for grasping and manipulation. However, this is not a trivial problem to solve d
YOLO: Real-Time Object Detection
How It Works Prior detection systems repurpose classifiers or localizers to perform detection. They apply the model to an image at multiple locations and scales. High scoring regions of the image are considered detections. We use a totally different approach. We apply a single neural network to the full image. This network divides the image into regions and predicts bounding boxes and probabilitie
CIFAR-10 and CIFAR-100 datasets
Baseline results You can find some baseline replicable results on this dataset on the project page for cuda-convnet. These results were obtained with a convolutional neural network. Briefly, they are 18% test error without data augmentation and 11% with. Additionally, Jasper Snoek has a new paper in which he used Bayesian hyperparameter optimization to find nice settings of the weight decay and ot
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OpenCV: OpenCV modules
ruby-opencvでプロ生ちゃん！ - Qiita
GitHub - ruby-opencv/ruby-opencv: Versioned fork of the OpenCV gem for Ruby