Results 11 to 20 of about 7,691,602 (298)
ITSA: An Information-Theoretic Approach to Automatic Shortcut Avoidance and Domain Generalization in Stereo Matching Networks [PDF]
Computer Vision and Pattern Recognition, 2022 State-of-the-art stereo matching networks trained only on synthetic data often fail to generalize to more challenging real data domains. In this paper, we attempt to unfold an important factor that hinders the networks from generalizing across domains ...
Weiqin Chuah +4 more
semanticscholar +1 more source
Local Similarity Pattern and Cost Self-Reassembling for Deep Stereo Matching Networks [PDF]
AAAI Conference on Artificial Intelligence, 2021 Although convolutional neural network based stereo matching architectures have made impressive achievements, there are still some limitations: 1) Convolutional Feature (CF) tends to capture appearance information, which is inadequate for accurate ...
Biyang Liu, Huimin Yu, Yangqi Long
semanticscholar +1 more source
Multi-scale Matching Networks for Semantic Correspondence [PDF]
IEEE International Conference on Computer Vision, 2021 Deep features have been proven powerful in building accurate dense semantic correspondences in various previous works. However, the multi-scale and pyramidal hierarchy of convolutional neural networks has not been well studied to learn discriminative ...
Dongyang Zhao +5 more
semanticscholar +1 more source
Stereo Object Matching Network [PDF]
2021 IEEE International Conference on Robotics and Automation (ICRA), 2021 This paper presents a stereo object matching method that exploits both 2D contextual information from images as well as 3D object-level information. Unlike existing stereo matching methods that exclusively focus on the pixel-level correspondence between stereo images within a volumetric space (i.e., cost volume), we exploit this volumetric structure in
Jaesung Choe +3 more
openaire +2 more sources
Topological Synthesis of Tree Shaped Structures Based on a Building Blocks Hypothesis
Journal of Telecommunications and Information Technology, 2023 In this paper a new approach to evolutionary controlled creation of electronic circuit connection topology is proposed. Microwave circuits consisting of a tree like connection of ideal transmission lines are considered. Assuming that a reasonable number
Przemysław Miazga
doaj +1 more source
Matching and Network Effects [PDF]
Journal of the European Economic Association, 2006 Individuals form teams to produce an output. The quality and quantity of a team's output depends on the ability and the effort level of its members. The ability of individuals as well as their work ethic is however imperfectly known. In such an environment, individuals wishing to form a new team can get information about each other from the network of ...
Marcel Fafchamps +2 more
openaire +3 more sources
SuperGlue: Learning Feature Matching With Graph Neural Networks [PDF]
Computer Vision and Pattern Recognition, 2019 This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points.
Paul-Edouard Sarlin +3 more
semanticscholar +1 more source
Design of High-Efficiency Matching Networks for Capacitive Wireless Power Transfer Systems
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2022 Matching networks are an efficient means of providing large voltage or current gain and reactive compensation in high-frequency wireless power transfer (WPT) systems. This article introduces an analytical optimization approach for the design of L-section
Sreyam Sinha +3 more
semanticscholar +1 more source
Bidirectional Stereo Matching Network With Double Cost Volumes
IEEE Access, 2021 In stereo matching, the high-quality cost volume is the key to improve the matching accuracy. Current stereo matching networks only use traditional methods or neural networks to generate one or more cost volumes.
Xiaogang Jia, Wei Chen, Zhengfa Liang
doaj +1 more source
Generative Moment Matching Networks for Genotype Simulation
bioRxiv, 2022 The generation of synthetic genomic sequences using neural networks has potential to ameliorate privacy and data sharing concerns and to mitigate potential bias within datasets due to under-representation of some population groups.
Maria Perera +5 more
semanticscholar +1 more source