Results 91 to 100 of about 242,783 (310)

Stereo Disparity through Cost Aggregation with Guided Filter

Image Processing On Line, 2014
Estimating the depth, or equivalently the disparity, of a stereo scene is a challenging problem in computer vision. The method proposed by Rhemann et al.
Pauline Tan, Pascal Monasse
doaj   +1 more source

Image Fusion for Super‐Resolution Mass Spectrometry Imaging of Plant Tissue

Advanced Science, EarlyView.
A loss controlled residual network (LCRN) workflow is developed for super‐resolution fusion of plant mass spectrometry imaging data. LCRN uses a novel edge perceptual loss metric to preserve complex plant tissue morphology. LCRN achieves up to 20‐fold magnification while effectively combining chemical information from mass spectrometry with ...
Yuchen Zou, Shipeng Sun, Weiwei Tang, Bin Li   +3 more
wiley   +1 more source

Oxygen‐Regulated GaN‐Based Sensors Fabricated by MOCVD for Switchable Gas Detection: Exhaled Gas Smart Platform for Non‐Invasive Disease Detection

Advanced Science, EarlyView.
This work presents highly consistent GaN‐based thin‐film gas sensors prepared by MOCVD for non‐invasive breath analysis. The sensors exhibit tunable selectivity from oxidizing to reducing gases by incorporating In composition, ultra‐low detection limits and humidity resistance.
Yuxuan Wang, Dan Han, Qi Duan, Zhekai Zhang, Zhengyang Jia, Juxu Guang, Guojing Wang, Weidong Wang, Xiuli He, Shengbo Sang   +9 more
wiley   +1 more source

Hemispherical Retina Emulated by Plasmonic Optoelectronic Memristors with All‐Optical Modulation for Neuromorphic Stereo Vision

Advanced Science
Binocular stereo vision relies on imaging disparity between two hemispherical retinas, which is essential to acquire image information in three dimensional environment.
Xuanyu Shan, Zhongqiang Wang, Jun Xie, Jiaqi Han, Ye Tao, Ya Lin, Xiaoning Zhao, Daniele Ielmini, Yichun Liu, Haiyang Xu   +9 more
doaj   +1 more source

Asymmetric occlusion detection using linear regression and weight‐based filling for stereo disparity map estimation

IET Computer Vision, 2016
Stereo matching computes the disparity information from stereo image pairs. A number of stereo matching methods have been proposed to estimate a fine disparity map.
T. Malathi, M. K. Bhuyan
doaj   +1 more source

AIEgen‐Based Proactive Early Warning System and Precise Treatment Strategy for Monkeypox Prevention and Control

Advanced Science, EarlyView.
An intelligent early warning and treatment system for monkeypox, utilizing a sprayable AIEgen‐ liquid dressing (AIE@LD) that responds to lesion pH. Integrated with a smartphone app and cloud platform, it enables real‐time infection detection via fluorescence imaging and triggers on‐demand photodynamic therapy under white light, effectively eradicating ...
Wei Wang, Zining Liu, Mengjun Li, Judun Zheng, Ruilin Zhang, Ke Liu, Xiaoxue Li, Shaoying Wen, Jingze Yu, Meijia Pan, Fengbo Ma, Kun Zhou, Zheng Zhao, Chenguang Shen, Yuhui Liao   +14 more
wiley   +1 more source

Stereo Vision for 3D Measurement in Robot Systems

Journal of Engineering and Sustainable Development, 2013
The major obstacle in the application of stereo vision to extract 3D information is the error in disparity map and highly computational cost at conventional computers.
Muhyi AL-Azawi, Dhafer R. Zaghar, Saba Ali Sadeq   +2 more
doaj  

P1-21: A Study on Stereoanomalies: Comparison of Upper and Lower Visual Field

i-Perception, 2012
Stereoanomalies suggest that some people lack disparity detectors or have a disorder of the subsystem associated with stereopsis and consequently fail to perceive correct depth.
Masahiro Ishii
doaj   +1 more source

Model of Cortical Cell Processing to Estimate Binocular Disparity

, 2013
International audienceThe starting point of our work are the physiological and psychophysical studies made on 3D vision, we attempt to build a model of stereoscopic vision.
Guyader, Nathalie, Guérin-Dugué, Anne, Maggia, Christophe   +2 more
core   +1 more source

UniMR: A Plug‐and‐Play Framework of Automated Molecular Recognition for Scanning Tunneling Microscopy

Advanced Science, EarlyView.
UniMR, a training‐free framework for automated molecular recognition in STM images. By integrating adaptive feature selection with CLIP embeddings and Gaussian Mixture Modeling, UniMR achieves robust performance across diverse molecular systems and low‐resolution conditions.
Ziqiang Cao, Lingyin Zhang, Bingzheng Wu, Haonan Chen, Junhao Sun, Linghao Yan, Wenfei Li, Yangyang Wu, Zhifang Wang, Qigang Zhong, Lifeng Chi   +10 more
wiley   +1 more source