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

Synthetic Data Tools and Software

The surge in demand for synthetic data generation is evident across various sectors, driven by stricter privacy regulations. As companies aim to leverage artificial intelligence (AI) responsibly, data creation platforms play a critical role in delivering privacy-safe datasets. These platforms serve a wide range of industries, including healthcare, finance, and

Computer vision

Industry Adoption of Synthetic Data: Case Studies and Trends

In a world overflowing with data, a significant shift is underway. By 2024, 60% of AI development data will be synthetic. The synthetic data market is rapidly expanding, expected to hit USD 2,339.8 million by 2030. This growth, with a CAGR of 35.3%, highlights synthetic data'

Data annotation

Comprehensive Guide to YOLOv10

The object detection algorithm YOLOv10 is one powerful innovation. It's 1.8 times faster than its predecessors, yet maintains similar accuracy. This is achieved with fewer parameters and FLOPs, marking a significant leap in the YOLO series. This advancement places YOLOv10 at the forefront of computer vision technology.

machine learning

Accessing Documentation and Support for Label Studio

Label Studio's architecture combines Python, Django, JavaScript, React, and Machine Learning backends. This makes it a versatile tool for various data types and multiple projects under one umbrella. Its installation process is straightforward, and components can be customized. The detailed Label Studio documentation empowers users to handle data

Machine learning

Comparing YOLOv10 with Other Object Detection Models

In the rapidly evolving field of computer vision, object detection models are critical for real-world applications. The introduction of YOLOv10 in May 2024 has set a new benchmark for efficiency and performance. It surpasses its predecessors by significantly reducing computational overhead and latency by 70% in its YOLOv10-N variant. This

Machine learning

Joining the Label Studio Community

Joining the Label Studio Community means entering a dynamic space that influences the future of machine learning. Discussions cover everything from data labeling to the latest in machine learning, fostering a culture of shared knowledge and contribution. With features that ensure all projects get the attention they need, you become

Data annotation

Deep Learning Frameworks for YOLOv10: PyTorch, TensorFlow, Keras

Frameworks such as PyTorch YOLOv10, TensorFlow YOLOv10, and Keras YOLOv10 are more than tools; they are drivers of innovation. They each have their own stories of challenges and victories in the YOLOv10 object detection field. YOLOv10 is changing the game with its non-maximum suppression (NMS) free-training and efficiency. You'