Data annotation & labeling blog.

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Maxim Dupont

Maxim Dupont is the founder of LabelVisor, a scientist & software engineer. His hobby of writing tech reviews has become his new way of life. His belief is that together we can achieve the best world.

Machine learning

Why is Data Annotation for Machine Learning and AI Important?

Data annotation for machine learning is often underestimated as an essential step in the overall process. Data annotation is the process of manually marking or labeling data. This way, you can use it to train machine learning algorithms. Imagine you have a website selling books. You want to recommend other

super-resolution images

A low-resolution display can produce super-resolution images using artificial intelligence-designed structured materials

In the field of augmented/virtual reality (AR/VR), one of the most promising technologies is holographic image displays that mimic 3D optical waves by using coherent light illumination. As a result of these holographic image displays, wearable displays may be able to simplify their optical setup, which may lead

AI and human planners

Cooperation between AI and human planners

Artificial intelligence allows supply chain planners to alter forecasts generated by self-learning systems. Are there any benefits to this? Would the software's forecast be more reliable than the human's? KLU researchers are addressing these questions in a state-of-the-art study. On average, their study found that human

Labeling

Labeling in the Data Annotation Process

Machine learning has become one of the most important areas of technological development in recent years. Companies have seen unimaginable growth and development using statistical methods to train algorithms. However, supervised machine learning algorithms still need human input to operate properly. Data annotation is the process by which training datasets

Сomputer vision

How to improve computer vision in a simpler manner

It is necessary to train a machine-learning model before it is capable of performing a specific task, such as identifying cancer from a medical image. In order to train an image classification model, millions of examples of images are presented in a massive dataset. In spite of this, using real

AI-based mirror

An AI-based mirror is driving consumers back to stores

Researchers have found that consumers feel embarrassment and fakeness when using digital makeup mirrors, as well as crave the "real" in-store experience. Based on the research conducted between 2018-2022 by Bayes Business School, this study examined psychological and sociological factors associated with consumer experience with Augmented Reality (AR)

Machine learning hardware that can be trained with an optical chip

Machine learning hardware that can be trained with an optical chip

Using a chip developed by a multi-institutional research team, machine learning hardware can be trained. The research was published in Optica 23.11.2022. A recent McKinsey report estimates that machine learning applications are worth $165 billion annually. However, before a machine is able to perform intelligence tasks such as