Výsledky vyhledávání - "hahmontunnistus (tietotekniikka)"

Automatic social distance estimation for photographic studies: Performance evaluation, test benchmark, and algorithm

Autor: Mert Seker, Anssi Männistö, Alexandros Iosifidis, Jenni Raitoharju

Publikováno v: Machine Learning with Applications. 10:100427

The social distancing regulations introduced to slow down the spread of COVID-19 virus directly affect a basic form of non-verbal communication, and there may be longer term impacts on human behavior and culture that remain to be analyzed in proxemic

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9b9089eb2d3d8088bb3b199b0962db25
https://doi.org/10.1016/j.mlwa.2022.100427

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BRIMA : Low-Overhead Browser-Only Image Annotation Tool

Autor: Lahtinen, Tuomo, Turtiainen, Hannu, Costin, Andrei

Image annotation and large annotated datasets are crucial parts within the Computer Vision and Artificial Intelligence fields. At the same time, it is well-known and acknowledged by the research community that the image annotation process is challeng

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______1222::b4405529f6fa864dca5d58964fdf1c81
http://urn.fi/URN:NBN:fi:jyu-202107284401

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Zero-shot Semantic Segmentation using Relation Network

Autor: Oleksiy Khriyenko, Yindong Zhang

Publikováno v: FRUCT
Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 28, Iss 1, Pp 516-527 (2021)

Zero-shot learning (ZSL) is widely studied in recent years to solve the problem of lacking annotations. Currently, most studies on ZSL are for image classification and object detection. But, zero-shot semantic segmentation, pixel level classification

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2cb126972da5d69e414f0f772af09b6c
http://urn.fi/URN:NBN:fi:jyu-202102161673

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Tree Species Identification Using 3D Spectral Data and 3D Convolutional Neural Network

Autor: Niko Viljanen, Leevi Annala, Samuli Rahkonen, Eija Honkavaara, Ilkka Pölönen, Teemu Hakala, Sakari Tuominen, Olli Nevalainen

Publikováno v: WHISPERS

In this study we apply 3D convolutional neural network (CNN) for tree species identification. Study includes the three most common Finnish tree species. Study uses a relatively large high-resolution spectral data set, which contains also a digital su

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b5dc6ab037bc14ab0eca1842e6cb94a1
http://urn.fi/URN:NBN:fi:jyu-202012117078

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