Named as a G2 2024 Spring High Performer and Easiest To Use in Data Labeling Software
Labellerr Using state-of-the-art AI, improves sports through accurate ball tracking, player security, and object recognition unique to each game. Join us in transforming sports analytics.
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With unmatched experience with computer vision for sports applications. Our state-of-the-art annotation services guarantee the highest level of accuracy for the study of sporting performance. Laborerr's tool and service enables automobile manufacturers minimise costs without sacrificing the highest calibre of automated annotation.
Accurate and timely analysis of ball trajectory in real-time for cricket and tennis players.
Identifying various athletic objects with ease for improved analysis.
Exceptionally accurate pinpointing of shuttlecock movement.
Tracking cyclist positions for performance analysis and safety precautions is known as cycling position detection.
As a pioneer in computer vision for sports applications, Labellerr provides accurate annotations for photos and videos in a range of sporting contexts.
The platform's expertise in sports data annotation enables the creation of extremely precise machine learning models. Labellerr is a key player in the advancement of sports analytics and safety compliance with its expertise in athlete tracking, object detection, and event recognition.
With a focus on player safety and equipment monitoring, Labellerr accurately annotates sports-related data to help ensure safety compliance in the industry.
Labellerr makes it easier to construct machine learning models that can track player movements, identify safety dangers, and improve overall safety measures in a variety of sports environments by providing accurate annotations in photos and videos.
Labellerr has demonstrated its efficacy in a number of sports production use cases, such as event recognition for improved sports broadcasting, equipment detection for safety compliance, and real-time athlete tracking for performance analysis.
Labellerr is essential to the development of machine learning models that drive innovation in sports analytics and improve the viewing experience overall since it provides precise annotations.
Labellerr's use of AI and computer vision has made a significant contribution to sports analytics. Labellerr makes it easier to train machine learning models for tasks like player tracking, action detection, and performance analysis by offering accurate annotations for sports-related data.
These models improve the capabilities of sports analytics and provide insightful information on team tactics, player behaviour, and game dynamics.
Using its computer vision capabilities, Labellerr is essential to sports cyclist position tracking and anomaly detection. Labellerr makes it easier to construct machine learning models that can detect and analyse rider positions in real time by precisely annotating photos and videos of cycling events.
This feature is crucial for sports analytics since it allows for precise performance evaluation and early anomaly detection during bicycle competitions.
Tensor Matics Inc
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Tensor Matics Pvt Ltd
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Phone: +917565883102
