The internet moves too fast for human-only moderation — and AI systems trained on human-labeled data now play a key role in detecting harmful content. But even with the best annotations, AI can miss context, nuance, and intent.
Waste Segregation in the Age of AI is taking center stage as urban growth and evolving consumption habits intensify the challenges of waste management. Traditional manual methods can no longer keep up, while AI offers a faster, more efficient solution if trained effectively.
Image Labeling Essentials is one of DeeLab Academy’s recently launched certification courses. This 5-day image annotation training focuses on core labeling methods used in machine learning—especially in computer vision tasks like object detection, pose estimation, and image segmentation.
In retail, artificial intelligence is changing how retail stores operate. From keeping shelves stocked to improving customer experiences, smart technology is making shopping more efficient. But behind these innovations is one key factor—data annotation. Without properly labeled data, even the best AI systems wouldn’t function correctly.
DeeLab offers a customizable training and certification program under DeeLab Academy—crafted to enhance skills and build expertise in data annotation and related fields.
Geospatial data, which links objects or features to a specific location on the Earth’s surface, plays a critical role in everything from urban planning and environmental management to navigation and autonomous systems.
Security is essential in both large and frequent spaces. AI security systems with object recognition strengthens protection by identifying potential threats, but its effectiveness depends on well-crafted training datasets that ensure accurate AI decisions.
The real estate industry faces significant challenges in ensuring property safety and structural soundness, with roof condition being a key concern. Roof annotation, which involves detailed marking and examination of roof images, plays a crucial role in this process.
Image segmentation is crucial for autonomous driving, enabling self-driving cars to accurately perceive and interpret their environment. This ensures the reliability and safety of these advanced automotive technologies.
Data annotation is pivotal in AI and machine learning. Meta’s Segment Anything model (SAM) revolutionizes the field, blending human intelligence with advanced algorithms for enhanced data accuracy and efficiency.