Data annotation & labeling blog.

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Maxim Dupont

Maxim Dupont is the founder of LabelVisor, a scientist & software engineer. His hobby of writing tech reviews has become his new way of life. His belief is that together we can achieve the best world.

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Best Practices for Data Annotation with Label Studio

The AI and machine learning model market is expected to surge at a 32.54% CAGR from 2020 to 2027. This rapid growth highlights the pivotal role of data annotation in AI progress. Label Studio, a leading open-source tool, is at the forefront of this data labeling evolution. Label Studio

Data annotation

Speed and Efficiency of YOLOv10

YOLOv10, the latest in the YOLO series, brings groundbreaking advancements. It eliminates non-maximum suppression (NMS) and optimizes model components. This results in superior YOLOv10 performance and reduced computational overhead. It addresses key limitations of previous versions, expanding the possibilities in object detection. With its state-of-the-art accuracy-latency trade-offs across multiple model

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Integrating Label Studio with Machine Learning Pipelines

Label Studio is more than just another tool in your AI toolkit. It's a game-changer that integrates seamlessly into your machine learning pipelines. This boosts AI performance and streamlines your workflow. Its modular design and extensible API make it adaptable to your needs, supporting various data types and

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Accuracy and Precision Improvements in YOLOv10

YOLOv10, the latest iteration in the YOLO (You Only Look Once) family, pushes the boundaries of object detection. It offers six size options ranging from N to X. This caters to diverse computational needs without compromising on accuracy. The groundbreaking NMS-free training approach introduces models that require up to 57%

Data annotation

Exporting Annotations from Label Studio

Exporting annotations from Label Studio is a pivotal step in the data annotation process. As you work through your machine learning data pipelines, knowing how to export your annotated data effectively is crucial. Label Studio provides powerful annotation export tools that simplify this process, ensuring your labeled datasets are prepared

Data annotation

Advanced Use Cases of YOLOv10

The architecture of YOLOv10 is meticulously designed to balance precision with computational efficiency. It incorporates innovative features like large-kernel convolutions and partial self-attention modules. These elements boost its performance without compromising on efficiency. This makes YOLOv10 a top choice for AI-powered surveillance and real-time tracking. YOLOv10's versatility is

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Collaboration Features in Label Studio

Label Studio stands out as a leading platform for team collaboration in data annotation projects. It simplifies your machine learning workflows with its advanced Collaboration Label Studio features. The tool supports a wide range of data types and offers templates for rapid project setup. This makes it perfect for teams