The Tenth Workshop on Fine-Grained Visual Categorization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F23%3A43971634" target="_blank" >RIV/49777513:23520/23:43971634 - isvavai.cz</a>

Výsledek na webu

<a href="https://sites.google.com/view/fgvc10/" target="_blank" >https://sites.google.com/view/fgvc10/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

The Tenth Workshop on Fine-Grained Visual Categorization

Popis výsledku v původním jazyce

Fine-grained categorization, the precise differentiation between similar plant or animal species, disease of the retina, architectural styles, etc., is an extremely challenging problem, pushing the limits of both human and machine ability. In these domains expert knowledge is typically required, and the question that must be addressed is how can we develop artificial systems that can efficiently discriminate between large numbers of highly similar visual concepts. The 10th Workshop on Fine-Grained Visual Categorization (FGVC10) will explore topics related to supervised learning, self-supervised learning, semi-supervised learning, matching, localization, domain adaptation, transfer learning, few-shot learning, machine teaching, multimodal learning (e.g., audio and video), 3D-vision, crowd-sourcing, image captioning and generation, out-of-distribution detection, anomaly detection, open-set recognition, human-in-the-loop learning, and taxonomic prediction, all through the lens of fine-grained understanding. Hence, the topics relevant for FGVC10 are neither restricted to vision nor categorization.

Název v anglickém jazyce

The Tenth Workshop on Fine-Grained Visual Categorization

Popis výsledku anglicky

Fine-grained categorization, the precise differentiation between similar plant or animal species, disease of the retina, architectural styles, etc., is an extremely challenging problem, pushing the limits of both human and machine ability. In these domains expert knowledge is typically required, and the question that must be addressed is how can we develop artificial systems that can efficiently discriminate between large numbers of highly similar visual concepts. The 10th Workshop on Fine-Grained Visual Categorization (FGVC10) will explore topics related to supervised learning, self-supervised learning, semi-supervised learning, matching, localization, domain adaptation, transfer learning, few-shot learning, machine teaching, multimodal learning (e.g., audio and video), 3D-vision, crowd-sourcing, image captioning and generation, out-of-distribution detection, anomaly detection, open-set recognition, human-in-the-loop learning, and taxonomic prediction, all through the lens of fine-grained understanding. Hence, the topics relevant for FGVC10 are neither restricted to vision nor categorization.

Druh

W - Uspořádání workshopu

CEP obor

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OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/SS05010008" target="_blank" >SS05010008: Detekce, identifikace a monitoring živočichů pokročilými metodami počítačového vidění</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Místo konání akce

Vancouver

Stát konání akce

CA - Kanada

Datum zahájení akce

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Datum ukončení akce

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Celkový počet účastníků

100

Počet zahraničních účastníků

99

Typ akce podle státní přísl. účastníků

WRD - Celosvětová akce