In today's dynamic digital landscape, data is pivotal in fueling innovations in artificial intelligence (AI). Video annotation is critical for advancements in AI through computer vision. Moreover, the training data must be customized per the AI model's training requirements for developing AI and machine learning (ML) applications. Video annotation aids ML models in … [Read more...] about Significance of Video Annotation in Training Computer Vision Models
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The Future of Image Annotation: Emerging Trends
The digital age has ushered in a wave of AI and ML advancements, yet the performance of many of these depends on image annotation. As we stand on the cusp of technological breakthroughs in computer vision, understanding the future of image annotation becomes vital to grasping the trends. Image annotation is a critical component in the building of computer vision systems and … [Read more...] about The Future of Image Annotation: Emerging Trends
How Organizations Can Leverage AI to Improve Recycling
Recycling is proving to be a big challenge for even the world's largest economies. According to recent data, more than 90 million tons of recyclable material are in United States landfills every year. One of the biggest reasons for this is that items that cannot be recycled are mixed in with the ones that can. In fact, it is estimated that, on average, 1 in every 4 items in … [Read more...] about How Organizations Can Leverage AI to Improve Recycling
Innovative ways AI drones are being used across industries
NDVI maps: Normalized Difference Vegetation Index (NDVI) takes the insights of an RGB map one step further. The map shows the amount of infrared light reflected in an area, which is an indicator of malnourishment and drought. According to Go Intelligence, this kind of data collection can be used to spot problem crops RGB maps: A birds-eye view but even better, even a basic … [Read more...] about Innovative ways AI drones are being used across industries
How to Use Pre-Labeled Data for AI Algorithms With High-Quality Requirements
In machine learning, data labeling is the process of identifying objects or events on raw data (images, text files, videos, etc.) and adding one or more meaningful and informative labels to provide context so that a machine learning model can learn from it. For example, labels might indicate whether a photo contains a bird or car, which words were uttered in an audio recording, … [Read more...] about How to Use Pre-Labeled Data for AI Algorithms With High-Quality Requirements
