Blog
Upalgo Labeling by Ezako is now distributed by Siemens
Ezako and XPERT: deep learning for every underwater platform
Ezako and XPERT start a development project to adapt neural networks to every underwater platform, from drones to hydrophones, and to improve the real-time detection of underwater anomalies.
Upalgo Labeling joins the Altair Partner Alliance
Altair distributes Upalgo Labeling through the Altair Partner Alliance: a tool to annotate time series and sensor data, with label propagation.
VASCREEN: detecting dangerous and illegal substances in luggage
Within the SecurIT programme, Ezako and MION develop VASCREEN, a solution to detect potentially dangerous and illegal substances in luggage and goods.
What can you do with time-series data?
What time-series data is, where it comes from, how machine learning puts it to work, and what return to expect from it.
Ezako joins the Minc Scale program
Ezako joins Minc Scale, a programme that supports growing companies with international ambitions, to approach the Nordic market.
Ezako joins NVIDIA Inception
Ezako joins NVIDIA Inception, the programme that supports startups working with artificial intelligence.
What is MTBF, and why does it matter?
The mean time between failures says how reliable a machine is: what it is, why it matters, how to calculate it and how to improve it.
Ezako and Alseamar: deep learning on autonomous underwater platforms
Within the RAPID project DASMIA, Ezako and Alseamar develop deep learning on autonomous underwater platforms.
What is federated learning?
Federated learning trains a shared model on data that stays on the devices that hold it: only the model’s updates travel. What it is, and when it is useful.
A deep learning approach to signal anomaly detection, with Safran Aircraft Engines
Abnormal observations in high-frequency sensor series can make the spectrograms of an engine test unusable. A deep learning approach to detect them, developed with Safran Aircraft Engines.