image transformation are some basic techniques to deal with images where we performs various procedure to make a image data to deal well with image modeling processes.
NVIDIA has submitted its training results for all eight benchmarks.
In template matching, we find out the location in the source image of the template image. Here we can understand that it is required to have the size of the source image larger than the template image.
Today in this article, we are going to discuss Deep labeling an algorithm made by Google. DeepLab is short for Deep Labeling, which aims to provide SOTA and an easy to use Tensorflow code base for general dense pixel labeling. DeepLab refers to solving problems by assigning a predicted value for each pixel in an image or video with the help of deep neural network support.
Facebook’s D2Go with in-built Detectron2 is the state-of-the-art toolkit for training & deployment of computer vision models on mobile devices
MMDetection is a Python toolbox built as a codebase exclusively for object detection and instance segmentation tasks
Image processing is carried out in all stages of Computer Vision such as preprocessing images, deep learning modeling and post-processing
Point Transformer reaches a new milestone in various public 3D image datasets by outperforming the present strongest models
PaddleSeg is an Image segmentation framework based on Baidu’s PaddlePaddle(Parallel Distributed Deep Learning). It provides high performance and efficiency, SOTA segmentation models optimized for MultiNode and MultiGPU production systems.
TransUNet, a Transformers-based U-Net framework, achieves state-of-the-art performance in medical image segmentation applications
Image segmentation forms the basis of numerous Computer Vision projects. It segments the visual input…
the development of better data annotator tools which can provide better accuracy, speed and precision in data annotations and thus today we’ll be discussing SuperAnnotate.