Data annotation & labeling blog.

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Data annotation

Data annotation

Data annotation is one of the important parts of machine learning, especially in AI example. To know more about this and get better knowledge on Data Annotation, we need to know ALL the basics! So, we will be putting up a blog on "Data Annotation" [AIN-103] with A - Z coverage which will help you in understanding different parts related to Annotation of data.

computer vision

Datasets for Training YOLOv10

YOLOv10, the latest in the YOLO family, marks a leap forward in object detection. It was unveiled on May 23, 2024, by researchers at Tsinghua University. This neural network significantly advances real-time object detection capabilities. This model showcases notable improvements in speed and efficiency. YOLOv10-S surpasses its predecessors, offering 1.

computer vision

Initial Configuration of Label Studio

Upon launching Label Studio for the first time, it employs an SQLite database for storing labeling tasks and annotations. This default setup is suitable for smaller projects. However, for larger projects, switching to PostgreSQL can enhance performance and scalability. The command line provides numerous arguments to personalize your Label Studio

computer vision

Core Algorithms and Techniques in YOLOv10

YOLOv10 represents a major advancement in real-time object detection. It builds upon the success of its predecessors, introducing new techniques that significantly enhance its performance across various applications. This latest version of the YOLO family showcases the power of deep learning and efficiency. The architecture of YOLOv10 includes NMS-free training

computer vision

Installation Guide for Label Studio

Welcome to the comprehensive Label Studio Installation Guide. This tutorial will guide you through setting up Label Studio, a powerful tool for data annotation. It supports both on-premises and cloud environments, offering various installation methods to meet your needs. Label Studio is compatible with Linux, Windows, and MacOSX systems, requiring

machine learning

Detailed Architecture of YOLOv10

YOLOv10, the latest in real-time object detection, represents a major advancement in convolutional neural networks. It was released in May 2024 and has redefined the computer vision landscape. This deep learning model addresses long-standing object detection challenges, offering unparalleled speed and accuracy. At its core, YOLOv10 employs a groundbreaking NMS-free

computer vision

The Importance of Data Annotation in Machine Learning

Data annotation is the cornerstone of AI and ML model development. It involves labeling raw data to create precise training datasets. This essential step imbues algorithms with the ability to discern patterns and predict outcomes. The global data annotation market is experiencing exponential growth, expected to hit $6,450.0

machine learning

History of YOLO: From YOLOv1 to YOLOv10

The YOLO (You Only Look Once) family has transformed computer vision since its debut in 2016. Joseph Redmon and his team introduced this groundbreaking framework, altering the real-time processing landscape in artificial intelligence. YOLO's inception started with YOLOv1, employing convolutional neural networks for swift object detection in images.