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.

Data annotation

Comparative Analysis of YOLO Versions: YOLOv1 to YOLOv10

In the vast realm of deep learning, YOLO (You Only Look Once) has emerged as a key innovation. It has impacted fields from gene expression to advanced agricultural systems. From the initial YOLOv1, which processed visual data at 45 frames per second, to the latest YOLOv10, which has significantly reduced

computer vision

Text Annotation for NLP with Label Studio

Label Studio offers a user-friendly platform for text annotation, supporting various NLP tasks like named entity recognition, sentiment analysis, and text classification. Its versatility allows you to tackle complex labeling tasks with ease, making it a go-to choice for NLP projects of all sizes. With Label Studio, you can streamline

machine learning

Future Trends and Developments in YOLO

As we look ahead, the future of YOLO promises even more impressive advancements in real-time object detection and computer vision applications. YOLO Vision 2024, an upcoming hybrid event scheduled for September, 2024, at Google for Startups Campus in Madrid, will showcase the latest YOLO features and object detection future. This

Data annotation

Using Label Studio for Autonomous Driving Video Annotation

Label Studio, a leading open-source data labeling tool, is favored by over 250,000 machine learning experts and data scientists globally. It has a significant role in transforming autonomous driving video annotation. Label Studio provides a comprehensive solution for annotating diverse data types, including video essential for self-driving vehicles. Its

Data annotation

Solutions and Workarounds for YOLOv10 Challenges

YOLOv10 brings impressive advancements to the table. With models ranging from Nano to Extra Large, it caters to diverse computational needs. The Nano version, with just 2.3 million parameters, achieves a remarkable 38.5% APval at a swift 1.84ms latency. On the other end, the X version boasts

Machine learning

Label Studio in Healthcare: Medical Image Annotation

Label Studio, with 18.2k stars on GitHub, is a top choice for medical image labeling. Its open-source nature and customizable features make it perfect for healthcare professionals looking for efficient ways to label medical datasets. The platform's flexibility allows for seamless integration with machine learning models. This

Data annotation

Common Issues in YOLOv10 Implementation

YOLOv10, the latest YOLO object detection framework, eliminates non-maximum suppression (NMS)? This could reduce latency by up to 30%. This breakthrough in real-time object detection has garnered significant interest from developers and researchers. Developed by Tsinghua University researchers, YOLOv10 introduces a new approach to object detection challenges. It uses Consistent