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AI for a Better Future: Our Highlights from CEATEC Japan

First hours at CEATEC Official.   This was my first time beeing in Japan. I expected lots of noise and tech overload. Instead, nothing but calm faces, precise conversations, quiet determination. Here, innovation doesn’t try to impress. It tries to endure. There’s something very Japanese in that: patience before progress. I’m here with INNOKREA, but […]

INNOKREA at EDAG Smart Industry Summit, Fulda 2025 – and what an event that was!

Promising beginnings   Already on our way to Fulda, we were in high spirits😊, as if everything was going to go our way. The plane was super punctual, we got our luggage after a few minutes of waiting as the first passengers, and we rented a car from our supplier at Frankfurt Airport without any […]

✨ Still buzzing with positive energy and inspiration after last week’s TechBBQ in Copenhagen!

INNOKREA knows many faces of Grilling😅. The classic one – social, with sausages, a cold drink, and the eternal question: “is it ready yet?”

Object Detection in Computer Vision

After the fundamentals of neural networks and image classification, it's time to delve into object detection. What exactly is it? How does it differ from simply assigning a label to the entire image? In this article, we'll not only answer these questions but also examine the practical application of the popular YOLO algorithm.

TNW Amsterdam 2025® in CEO’s eyes: the future of innovative technologies

🔥 Hot news from Amsterdam! Innovation, lots of good conversations... and memories of a silent bartender.🤷‍♂️💡

Train Faster, Smarter, Better – On Techniques for Training Neural Network Models

Commonly used neural network training optimisation techniques: Transfer Learning, Domain Adaptation and Data Augmentation.

How to Hack, How to Improve a Neural Network?

Active learning as a way to effectively reduce the cost and time required to label training data for neural networks.

Neural Networks Through Magnifying Glass

Neural networks- learn the details of their training, from activation functions to back propagation.

Artificial Neural Networks: how to train them?

Artificial neural networks - discover the stages of their training, starting with the data, through the learning process to testing the model.

Neural networks – introduction

Discover the depths of deep learning with us! In this article, you will learn what secrets neural networks hide.

Neural Networks Training with Limited Resources

Neural networks and their training on graphics processing units (GPUs). Learn why GPUs are becoming a popular choice.

Machine Learning – Part 3: Data Representation Methods

Several widely used data representation methods - how to effectively transfer data to the data processing algorithm.

Machine Learning – Part 2: Different Approaches

About the approaches used in this field, their advantages and disadvantages, as well as possible applications of some algorithms.

Machine Learning – Part 1: Is It Worth It?

Machine learning is a field that is developing at an incredible pace and is penetrating virtually all sectors of the economy.