There can be no doubt that data is the life blood in today’s high-octane high-speed environment of artificial intelligence (AI). The capability of a machine learning framework is more or less directly ...

Type dienstverband: Internship and graduation project Locatie: Den Haag Opleidingsniveau: Master Uren per week: Fulltime - 40 What will be your role?

(2020) is a deep learning-based segmentation model particularly suitable for salient object detection and segmentation tasks ... responsible for extracting semantic features from the image, typically ...

Think smarter object recognition, better lane tracking, and faster hazard detection. At the same time, V2X allows your car to talk to traffic lights, other vehicles, and even pedestrians’ mobile ...

This method is built on a lightweight dual-stream semantic segmentation model called AttnGPRNet, developed in this work to improve feature extraction through attention mechanisms and enhance ...

We propose the first explainable image forgery detection and localization (e-IFDL) task, addressing the opacity of traditional IFDL methods by providing both pixel-level and semantic-level ...

Abstract: A thermal fault detection method for High-speed direct-driven blower components is proposed, utilizing thermal and visible image fusion along with semantic segmentation. The proposed method ...

FTW is an order of magnitude larger than previous datasets with 70,462 samples, each containing instance and semantic segmentation masks paired with multi-date, multi-spectral Sentinel-2 satellite ...

Instance Approximator: instance approximation algorithms to extract instances from semantic segmentation maps/model outputs. Instance Matcher: matches predicted instances with reference instances.

Our results demonstrate that MSU-Net built by integrated multiple convolution sequences with different receptive fields enables significant improvement of semantic segmentation ... This improvement ...