Results 61 to 70 of about 44,407 (267)

Semantic segmentation using GSAUNet

ICT Express, 2023
Gabor filters well support computer vision tasks due to its steerable properties, that are useful for handling image transformation such as image rotation and image scaling. In this paper, the Gabor-based UNet (GSAUNet) model is proposed where the Gabor filters replace the few default filters in the UNet.
Sangita B. Nemade, Shefali P. Sonavane
openaire   +2 more sources

Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay, Merve Alaylioglu, Erdi Sahin, Sanem Sultan Yoruk Oner, Gulce Iskan, Gulce Cosku Yilmaz Cakan, Gozde Kizilates‐Evin, Emre Hari, Elif Kurt, Erdinc Dursun, Basar Bilgic, Hasmet Hanagasi, Hakan Gurvit, Tamer Demiralp, Duygu Gezen‐Ak, Bedia Samanci   +15 more
wiley   +1 more source

Multi‐similarity based hyperrelation network for few‐shot segmentation

IET Image Processing, 2023
Few‐shot semantic segmentation aims at recognizing the object regions of unseen categories with only a few annotated examples as supervision. The key to few‐shot segmentation is to establish a robust semantic relationship between the support and query ...
Xiangwen Shi, Zhe Cui, Shaobing Zhang, Miao Cheng, Lian He, Xianghong Tang   +5 more
doaj   +1 more source

NFDI MatWerk Ontology (MWO): A BFO‐Compliant Ontology for Research Data Management in Materials Science and Engineering

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, Ebrahim Norouzi, Kostiantyn Hubaiev, Jörg Waitelonis, Harald Sack   +4 more
wiley   +1 more source

PTRSegNet: A Patch-to-Region Bottom–Up Pyramid Framework for the Semantic Segmentation of Large-Format Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Semantic segmentation is a basic task in the interpretation of remote sensing images. Mainstream deep-learning-based semantic segmentation algorithms typically process images with small sizes.
Shiyan Pang, Yepeng Shi, Hanchun Hu, Lizhi Ye, Jia Chen   +4 more
doaj   +1 more source

WAILS: Watershed Algorithm With Image-Level Supervision for Weakly Supervised Semantic Segmentation

IEEE Access, 2019
Image semantic segmentation has great development in many fields, and the lack of fully supervised segmentation labels has always been a major problem in the development of image semantic segmentation.
Hongming Zhou, Kang Song, Xianglei Zhang, Wenyong Gui, Qiusuo Qian   +4 more
doaj   +1 more source

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, Prithwish Tarafder, Anton Wiberg, Huanyu Li, Johan Moverare, Patrick Lambrix   +5 more
wiley   +1 more source

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, Moritz Blum, Luana Caron, Alisa Chirkova, Philipp Cimiano, Basil Ell, Inga Ennen, Michael Feige, Maik Gaerner, Thomas Hilbig, Andreas Hütten, Günter Reiss, Tapas Samanta, Sonja Schöning, Christian Schröder, Lennart Schwan, Chris Taake, Martin Wortmann   +17 more
wiley   +1 more source

Is an Apple an Orange? A Large Language Model Benchmark for Candidate Term Extraction and Subclass Decisions Against Upper Ontologies in Engineering and Materials Science

Advanced Engineering Materials, EarlyView.
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch, Maximilian Holland, Klaus Drechsler, Johannes Schilp   +3 more
wiley   +1 more source

Causal unsupervised semantic segmentation

Pattern Recognition
Unsupervised semantic segmentation aims to achieve high-quality semantic grouping without human-labeled annotations. With the advent of self-supervised pre-training, various frameworks utilize the pre-trained features to train prediction heads for unsupervised dense prediction.
Junho Kim, Byung-Kwan Lee, Yong Man Ro
openaire   +2 more sources