Results 81 to 90 of about 109,180 (287)

Organ‐Specific and Conserved Regulatory Logic Orchestrates Gene Expression in the Embryonic Mesothelium

open access: yesAdvanced Science, EarlyView.
Integrated multi‐omic profiling maps the gene‐regulatory landscape of the coelomic mesothelium across heart, lung, and pancreas. A cardiac‐restricted regulatory program is uncovered in which TBX20 activates heart mesothelial (epicardial) cis‐regulatory elements, while MAF emerges as a conserved regulator of mesothelial identity.
Quang Minh Dang   +3 more
wiley   +1 more source

Research on wave measurement and simulation experiments of binocular stereo vision based on intelligent feature matching

open access: yesFrontiers in Marine Science
Waves are crucial in ocean observation and research. Stereo vision-based wave measurement, offering non-contact, low-cost, and intelligent processing, is an emerging method. However, improving accuracy remains a challenge due to wave complexity.
Junjie Wu   +30 more
doaj   +1 more source

MSCS: MeshStereo with Cross‐Scale Cost Filtering for fast stereo matching

open access: yesIET Computer Vision, 2018
MeshStereo (MS) and cross‐scale cost filtering (CSCF) are two most recently celebrated models for stereo matching. On one hand, MS model enlightens for fast solving the dense stereo correspondence problem according to a region‐based opinion. On the other
Peng Yao   +3 more
doaj   +1 more source

An Efficient Dense Stereo Matching Method for Planetary Rover

open access: yesIEEE Access, 2019
Stereo matching is one of the most important and challenging subjects in the field of planetary rover with a stereo vision system. The generated disparity map can make rover to avoid the obstacle and explore the planetary surface automatically.
Haichao Li, Liang Chen, Feng Li
doaj   +1 more source

Match-Stereo-Videos: Bidirectional Alignment for Consistent Dynamic Stereo Matching

open access: yes
Dynamic stereo matching is the task of estimating consistent disparities from stereo videos with dynamic objects. Recent learning-based methods prioritize optimal performance on a single stereo pair, resulting in temporal inconsistencies. Existing video methods apply per-frame matching and window-based cost aggregation across the time dimension ...
Jing, Junpeng   +2 more
openaire   +2 more sources

Intracellular Aβ42 Sequestration by a Serine Protease Mitigates Neurotoxicity in a Drosophila Alzheimer's Disease Model

open access: yesAdvanced Science, EarlyView.
Emerging evidence suggests that intraneuronal Aβ accumulation represents an early pathogenic event in Alzheimer's disease (AD). Using Drosophila AD model, this study shows that a nonsecreted serine protease Yip7 physically interacts with Aβ. This causes intraneuronal Aβ accumulation but surprisingly reduces the associated neurotoxicity, arguing that ...
Jingyun Su   +4 more
wiley   +1 more source

Stereo Imaging Using Hardwired Self-Organizing Object Segmentation

open access: yesSensors, 2020
Stereo vision utilizes two cameras to acquire two respective images, and then determines the depth map by calculating the disparity between two images.
Ching-Han Chen   +3 more
doaj   +1 more source

The stereo matching algorithm based on an improved adaptive support window

open access: yesIET Image Processing, 2022
In binocular stereo matching, there has been a problem of low matching accuracy and noise immunity in discontinuous regions and weak‐textured regions. This paper proposes a stereo matching algorithm based on an improved adaptive support window.
Jiyang Qi, Liang Liu
doaj   +1 more source

Investigating the performance of Correspondence Algorithms in Vision based Driver-assistance in Indoor Environment

open access: yes, 2012
This paper presents the experimental comparison of fourteen stereo matching algorithms in variant illumination conditions. Different adaptations of global and local stereo matching techniques are chosen for evaluation The variant strength and weakness of
Haider, Syed. M. B.   +2 more
core   +1 more source

Pyramid Stereo Matching Network [PDF]

open access: yes2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018
Recent work has shown that depth estimation from a stereo pair of images can be formulated as a supervised learning task to be resolved with convolutional neural networks (CNNs). However, current architectures rely on patch-based Siamese networks, lacking the means to exploit context information for finding correspondence in illposed regions. To tackle
Chang, Jia-Ren, Chen, Yong-Sheng
openaire   +2 more sources

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