Results 51 to 60 of about 32,830 (265)
Semantic Image Segmentation in Duckietown
Vestnik NSU. Series: Information Technologies, 2021 The article is devoted to evaluation of the applicability of existing semantic segmentation algorithms for the “Duckietown” simulator. The article explores classical semantic segmentation algorithms as well as ones based on neural networks. We also examined machine learning frameworks, taking into account all the limitations of the “Duckietown ...
D. E. Shabalina +3 more
openaire +2 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
Scalable Cascade Inference for Semantic Image Segmentation [PDF]
Procedings of the British Machine Vision Conference 2012, 2012 Semantic image segmentation is a problem of simultaneous segmentation and recognition of an input image into regions and their associated categorical labels, such as person, car or cow. A popular way to achieve this goal is to assign a label to every pixel in the input image and impose simple structural constraints on the output label space.
Sturgess, P +3 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
IEEE Access, 2023 In this paper, we propose novel convolutional encoder-decoder architectures for real-time semantic segmentation based on an image-to-image translation approach via the space-to-depth and depth-to-space modules.
Hatem Ibrahem +2 more
doaj +1 more source
Adversarial Examples for Semantic Image Segmentation
CoRR, 2017 ICLR 2017 workshop ...
Volker Fischer 0003 +3 more
openaire +3 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 +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
Advanced Engineering Materials, EarlyView.We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source