Data Explorer is a platform that was built to allow us focus on the data, curate it, clean it and make sure we start the development cycles with a great foundation.
Use Data Explorer in the Kaggle RSNA Mammography competition or EDA and coreset selection
As new uses for cameras and the visual data created become available, the need for tools to find the most valuable subsets becomes essential.
This article was originally published on InsideBigData. It is time to shift from a model-centric mindset to a data-centric approach. AI is a massive part of human life today and is woven into the fabric of our everyday society. From medical imagery scanning to the ubiquity of facial recognition software in our cell phones, AI […]
The challenge Imagine you’ve just been given a new batch of 10,000 images or hours of video and you need to find only a small portion of relevant images. How would you go about isolating that subset of the data? In many cases, we receive a batch of visual data, images or video, with very […]
ECCV 2022 was a truly remarkable event. With two full days of incredible workshops and tutorials, followed by three additional days of the main conference, Computer Vision was celebrated in every corner. During the conference, giants like Amazon, Google and Meta, giants-in-the-making like Akriadata, and a whole host of awesome companies gathered to present intriguing […]
nuScenes is a public dataset for autonomous driving. In this post, we'll break down how Akridata Data Explorer makes exploration easy.
The autonomous world is one of the most important developments in human history. From self driving cars to retail stores to warehouses, AI and machine learning are now an integral part of our everyday life, and the next frontier for AI is to enable machines to have even more autonomy. An essential component to bring […]
Class imbalance-in-visual data sets is an all too common problem in real-world applications that use machine learning and AI. Many applications of computer vision suffer from imbalanced class distribution, including fraud detection, anomaly detection, medical diagnosis, oil spillage detection, facial recognition, and more. The consequences of imbalanced class data can have serious impacts on model […]
AI and ML have made incredible strides in recent years, but we are rapidly approaching a critical impasse. For modeling and AI/ML infrastructure to continue progressing and succeed in real-world applications, improving the quality of data is the only way to make it possible. As Andrew Ng has recently campaigned, we now need to make […]