Results 61 to 70 of about 12,040,618 (293)
Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Advanced content-based semantic scene analysis and information retrieval: the SCHEMA project [PDF]
, 2003 The aim of the SCHEMA Network of Excellence is to bring together a critical mass of universities, research centers, industrial partners and end users, in order to design a reference system for content-based semantic scene analysis, interpretation and ...
I. KOMPATSIARIS +18 more
core +2 more sources
CCNR: Cross-regional context and noise regularization for SAR image segmentation
International Journal of Applied Earth Observations and Geoinformation, 2023 Semantic segmentation, a fundamental research direction in synthetic aperture radar (SAR) image interpretation, has significant application value for multiple sectors. However, noise, multi-style terrains, geometric distortion, and shadows make SAR image
Zitong Wu +6 more
doaj +1 more source
SEMANTIC SEGMENTATION OF AERIAL IMAGES WITH AN ENSEMBLE OF CNNS [PDF]
ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2016 This paper describes a deep learning approach to semantic segmentation of very high resolution (aerial) images. Deep neural architectures hold the promise of end-to-end learning from raw images, making heuristic feature design obsolete. Over the last decade this idea has seen a revival, and in recent years deep convolutional neural networks (CNNs) have
D. Marmanis +5 more
openaire +6 more sources
A Knowledge‐Based Approach for Understanding and Managing Additive Manufacturing Data
Advanced Engineering Materials, EarlyView.Additive manufacturing processes generate a large amount of data. Effectively managing, understanding, and retrieving information from this data remains a major challenge. Therefore, we propose an ontology‐based approach to integrate heterogeneous data, enable semantic queries, and support decision‐making.
Mina Abd Nikooie Pour +5 more
wiley +1 more source
Semantic Segmentation for Urban-Scene Images
CoRR, 2021 Urban-scene Image segmentation is an important and trending topic in computer vision with wide use cases like autonomous driving [1]. Starting with the breakthrough work of Long et al. [2] that introduces Fully Convolutional Networks (FCNs), the development of novel architectures and practical uses of neural networks in semantic segmentation has been ...
openaire +2 more sources
Dense Semantic Image Segmentation with Objects and Attributes [PDF]
2014 IEEE Conference on Computer Vision and Pattern Recognition, 2014 The concepts of objects and attributes are both important for describing images precisely, since verbal descriptions often contain both adjectives and nouns (e.g. 'I see a shiny red chair'). In this paper, we formulate the problem of joint visual attribute and object class image segmentation as a dense multi-labelling problem, where each pixel in an ...
Shuai Zheng 0001 +6 more
openaire +2 more sources
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Depth Density Achieves a Better Result for Semantic Segmentation with the Kinect System
Sensors, 2020 Image segmentation is one of the most important methods for animal phenome research. Since the advent of deep learning, many researchers have looked at multilayer convolutional neural networks to solve the problems of image segmentation.
Hanbing Deng +3 more
doaj +1 more source
Complexity, 2021 With the emergence of deep learning, computer vision has witnessed extensive advancement and has seen immense applications in multiple domains. Specifically, image captioning has become an attractive focal direction for most machine learning experts ...
Ariyo Oluwasammi +7 more
doaj +1 more source