Results 11 to 20 of about 5,366,983 (311)
Adaptive estimation of quantum observables [PDF]
Quantum, 2021 The accurate estimation of quantum observables is a critical task in science. With progress on the hardware, measuring a quantum system will become increasingly demanding, particularly for variational protocols that require extensive sampling.
Ariel Shlosberg +5 more
semanticscholar +1 more source
BinsFormer: Revisiting Adaptive Bins for Monocular Depth Estimation [PDF]
IEEE Transactions on Image Processing, 2022 Monocular depth estimation (MDE) is a fundamental task in computer vision and has drawn increasing attention. Recently, some methods reformulate it as a classification-regression task to boost the model performance, where continuous depth is estimated ...
Zhenyu Li +3 more
semanticscholar +1 more source
INS/Odometer Land Navigation by Accurate Measurement Modeling and Multiple-Model Adaptive Estimation [PDF]
IEEE Transactions on Aerospace and Electronic Systems, 2020 Land vehicle navigation based on the inertial navigation system (INS) and odometers (ODs) is a classical autonomous navigation application and has been extensively studied over the past several decades.
O. Wei, Yuanxin Wu, HongYue Chen
semanticscholar +1 more source
Boosting Monocular Depth Estimation Models to High-Resolution via Content-Adaptive Multi-Resolution Merging [PDF]
Computer Vision and Pattern Recognition, 2021 Neural networks have shown great abilities in estimating depth from a single image. However, the inferred depth maps are well below one-megapixel resolution and often lack fine-grained details, which limits their practicality.
S. Mahdi H. Miangoleh +4 more
semanticscholar +1 more source
AdaBins: Depth Estimation Using Adaptive Bins [PDF]
Computer Vision and Pattern Recognition, 2020 We address the problem of estimating a high quality dense depth map from a single RGB input image. We start out with a baseline encoder-decoder convolutional neural network architecture and pose the question of how the global processing of information ...
Shariq Farooq Bhat +2 more
semanticscholar +1 more source
Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation [PDF]
IEEE International Conference on Computer Vision, 2021 Domain adaptation for semantic segmentation aims to improve the model performance in the presence of a distribution shift between source and target domain.
Qin Wang +4 more
semanticscholar +1 more source
International Journal of Robust and Nonlinear Control, 2020 This article deals with the problem of adaptive estimation, that is, the simultaneous estimation of the state and time‐varying parameters, in the presence of measurement noise and state disturbances, for a class of uncertain nonlinear systems.
R. Franco +3 more
semanticscholar +1 more source
Adaptive Surface Normal Constraint for Depth Estimation [PDF]
IEEE International Conference on Computer Vision, 2021 We present a novel method for single image depth estimation using surface normal constraints. Existing depth estimation methods either suffer from the lack of geometric constraints, or are limited to the difficulty of reliably capturing geometric context,
Xiaoxiao Long +6 more
semanticscholar +1 more source
Sparse SIR: Optimal rates and adaptive estimation
, 2020 Sliced inverse regression (SIR) is an innovative and effective method for sufficient dimension reduction and data visualization. Recently, an impressive range of penalized SIR methods has been proposed to estimate the central subspace in a sparse fashion.
Kai Tan, Lei Shi, Zhou Yu
semanticscholar +1 more source
Cooperative interception with fast multiple model adaptive estimation
, 2020 For the case that two pursuers intercept an evasive target, the cooperative strategies and state estimation methods taken by pursuers can seriously affect the guidance accuracy for the target, which performs a bang For the case that two pursuers ...
Wang Shaobo +4 more
semanticscholar +1 more source