(CNNs), a deep learning technique calledsemantic segmentationlets you associate every pixel of an image with a class label. Applications for semantic segmentation include autonomous driving, industrial inspectio
Semantic segmentation is one of three sub-tasks in the overall process of image segmentation that helps computers understand visual information.
Instance segmentation is the task of detecting and segmenting objects in images. See different approaches to instance segmentation, including Mask R-CNN.
For business applications, clustering is a battle-tested tool in market segmentation and fraud detection. Clustering is also useful for categorizing documents, making product recommendations and in other applications where grouping entities makes sense. This article is part of Types of clustering algorithm...
Template matching: This technique uses a small image, or template, to find matching regions in a larger image. Image segmentation and blob analysis: This uses simple object properties, such as size, color, or shape. Tip: Typically, if an object can be recognized using a simple approach like...
Computer vision.Pretrained models are useful for training computer vision tasks like image segmentation,facial recognitionand object detection, if the source and target tasks are related. Speech recognition.Models previously trained on large speech data sets are useful for creating more versatile models....
and identify patterns on its own. This resulting model then can be applied to incoming data. An example of unsupervised learning is a customer segmentation model, which can take patterns in large data sets of customer usage and purchase history to cluster customers into groups for marketing ...
what is the simplified steps to add new language support to this project? What type of datasets are needed to be add my language support? And how much? (Both simple voice cloning and cross lingual voice conversion) What is the requirement of datasets? (For example segmentation, Tokenizer prep...
We introduce a novel distinctiveness analysis of a set of portraits, which leverages the deep features extracted by a pre鈥恡rained face recognition CNN and a hair segmentation FCN, in the context of a weakly supervised metric learning scheme. Our analysis enables the generation of a polarized ...
Instance segmentation (also known as image segmentation) is the computer vision task of recognizing objects in images along with their associated shape. It's useful in cases where you need to measure the size of detected objects, cut them out of their background, or more accurately detect oblon...