Search Results for "support" - Page 2

The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.

R-FCN (“Region-based Fully Convolutional Networks”) is an object detection framework that makes almost all computation fully convolutional and shared across the image, unlike prior region-based approaches (e.g. Faster R-CNN) which run per-region sub-networks. The repository provides an implementation (in Python) supporting end-to-end training and inference of R-FCN models on standard datasets. The authors propose position-sensitive score maps to reconcile the need for translation variance...

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.

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...

The STAIR Vision Library (SVL), originally developed to support the STanford AI Robot, provides software infrastructure for computer vision, machine learning, and probabilistic graphical models.