Artificial Intelligence (AI) is driving the future, and you should be ready for it to have a competitive advantage.
Machine learning (ML) is a subset of AI that provides software applications with the ability to detect patterns and make accurate predictions. ML gave us self-driving cars, email spam filtering, traffic detection, and more.
To train the highest-quality ML models, you need to feed their algorithm with accurate labeled data.
This blog post covers everything you need to know about data labeling to make informed decisions for your business. Here are the questions that this blog post will be answering:
AEDIT builds user-first technology that transforms complicated medical information into easy-to-use tools and engaging resources to empower users throughout their aesthetic journey.
Founded by a double board-certified facial plastic and reconstructive surgeon, AEDIT simplifies and safeguards the search for aesthetic solutions and qualified providers. As a single trusted source, AEDIT offers unbiased, medically verified content to educate users before connecting them with vetted, board-certified aesthetic providers.
Our on-demand booking tool allows users to instantly schedule appointments with providers in our network.
AEDIT needed a platform where they could perform facial and landmark detection and have direct oversight over the annotation…
Spacept uses AI to analyze satellite images to prevent fires and power outages caused by extreme weather. Their smart solution is fast, sustainable, and decreases the time and cost needed for infrastructure inspection.
Global warming is increasingly affecting infrastructure, meaning that inspections are more frequently needed. Spacept tried different annotation platforms for their satellite imagery annotation projects. They were searching for a platform where they can both create high-quality annotations and hire expert annotators.
Spacept, like many other computer vision companies, was in need of high-quality outsourced annotators to work on their large-scale projects. …
IntelinAir uses the power of aerial imagery analytics, computer vision, deep learning, and mobile technology to deliver real-time, data-driven decision support to farmers, which helps them manage their operations more effectively.
IntelinAir was building pixel-accurate annotations for their aerial imagery annotation projects. They were searching for a platform that could deliver higher-quality annotations in less time.
IntelinAir has a wide range of annotation projects. Everything from parcel segmentation, crop detection, and plant/tree/flower counting. Many of these tasks have complex, pixel-accurate annotation requirements. IntelinAir built an in-house tool and explored other platforms previously, but was looking for a way to dramatically…
Altris AI applies computer vision and deep learning algorithms to build real-time innovative ophthalmology diagnosis support for automatic, structural, and quantitative analysis as well as detection of retinal diseases on Optical Coherence Tomography (OCT) scans.
Civil infrastructure such as bridges and tunnels are directly related to the overall economic and demographic growth of countries all over the world. The majority of these infrastructures are becoming older and they are increasingly prone to catastrophic failures that result in loss of lives and high costs. To prevent infrastructure damage and failure, stringent safety regulations have been recently defined. For this reason, more efficient monitoring systems are required by road administrators to determine the health and safety level of tunnels, bridges, and other infrastructures.
In general, cracks are associated with concrete degradation and reinforcement corrosion which reduces the…
Percepto is a leading provider of autonomous drone-in-a-box solutions for monitoring and securing critical infrastructure and industrial sites. Our advanced, AI-based software provides real-time insights, aiding our customers to assess risk, minimize downtime, drive efficiency, and reduce operational costs without human intervention. Tested in all weather conditions, it is the most rugged platform available today.
Image annotation is the process of selecting objects in images and labeling the objects with classes, attributes, and tags to build a set of training data for machine learning models. Preparing image data in this fashion is the backbone of computer vision AI. For example, in order to build a computer vision model to recognize roof types in satellite images, one needs to annotate tens of thousands to millions of images of roofs in different cities, weather conditions, etc.
In this post, I will be introducing SuperAnnotate’s new free-to-use desktop app, discuss some of the reasons why we built it, and share more about many of the features which we feel will dramatically increase the speed, accuracy, and efficiency of annotation projects. There is a massive functionality gap between free and commercial image annotation tools. SuperAnnotate Desktop is closing this gap by providing the fastest all-inclusive software tool for computer vision engineers to complete their annotation tasks.
Vision-based AI automation industries have massive needs for training data, which is typically prepared by professional annotation service providers or internal annotation teams.
Managing such teams has become more and more challenging due to the ongoing pandemic that is forcing teams to work from home. As a result, annotation teams are finding it difficult to maintain the same quality and delivery speed as they did in the office.
In this article, we propose team management techniques for computer vision engineers and service companies to deliver and ensure fast and high-quality annotations.