Bounding Box Annotation
Bounding box annotation is the most commonly used annotation technique for training Machine Learning and Computer Vision models. DigiAcceron offers both 2D&3D bounding box annotations, Polygonal annotations and Cuboidal annotations
The Autonomous Vehicle industry is booming. Unlike other form of annotations, the AV industry requires high precision annotation services to effectively train their self driving vehicles. We help our clients with high quality annotation data that includes identifying objects in a road scene, traffic lights, pedestrian crossing, road signs, obstacles etc.
We help our clients with annotating the images acquired by satellite, drones, GPS and GIS systems. This type of annotation data will be mostly useful for conducting aerial survey, measuring deforestation etc. We use variety of techniques like bounding boxes and semantic segmentation to annotate objects such as buildings, water bodies, forest, agricultural land, solar panels etc.
This technique involves annotating the object at the pixel level. Mostly used deep learning algorithms where high precision data is required to train the models. With Semantic Segmentation each part of an object is annotated with class labels
In this technique the content of the video is annotated with required parameters. Whether you want to track the amount of time a particular brand name displayed during basketball match, or time of ball possession by host and opponent teams in a football match etc. can be tracked accurately by our annotators
Image annotation and tagging is the process of annotating the objects found in the image and tagging them with appropriate name. This technique is widely used by the retail industry and image recognition companies. For example, with image recognition techniques a retail firm can monitor their OOS without any manual intervention. We provide image annotation and labelling services to all type of industry verticals based on their unique needs