Results 121 to 130 of about 278,436 (276)
Vision‐Assisted Avocado Harvesting with Aerial Bimanual Manipulation
This work outlines the design and implementation of a bimanual aerial robot that employs visual perception and learning to detect, reach, and harvest avocados. A new gripper and fixer arm assembly is used to harvest avocados, while visual perception enables the detection of avocados and estimation of their position and orientation for determining ...
Zhichao Liu +3 more
wiley +1 more source
“Seeing” Beneath the Clouds—Machine‐Learning‐Based Reconstruction of North African Dust Plumes
Mineral dust is one of the most abundant atmospheric aerosol species and has various far‐reaching effects on the climate system and adverse impacts on air quality.
Franz Kanngießer, Stephanie Fiedler
doaj +1 more source
A Multi-Level SAR-Guided Contextual Attention Network for Satellite Images Cloud Removal
In the field of remote sensing, cloud cover severely reduces the quality of satellite observations of the earth. Due to the complete absence of information in cloud-covered regions, cloud removal with a single optical image is an ill-posed problem. Since
Ganchao Liu, Jiawei Qiu, Yuan Yuan
doaj +1 more source
Flexible Sensor‐Based Human–Machine Interfaces with AI Integration for Medical Robotics
This review explores how flexible sensing technology and artificial intelligence (AI) significantly enhance human–machine interfaces in medical robotics. It highlights key sensing mechanisms, AI‐driven advancements, and applications in prosthetics, exoskeletons, and surgical robotics.
Yuxiao Wang +5 more
wiley +1 more source
A Continuous Low-Rank Tensor Approach for Removing Clouds from Optical Remote Sensing Images
Optical remote sensing images are often partially obscured by clouds due to the inability of visible light to penetrate cloud cover, which significantly limits their subsequent applications. Most existing cloud removal methods formulate the problem using
Dong-Lin Sun +3 more
doaj +1 more source
A parameterization of size resolved below cloud scavenging of aerosols by rain [PDF]
A size dependent parameterization for the removal of aerosol particles by falling rain droplets is developed. Scavenging coefficients are calculated explicitly as a function of aerosol particle size and precipitation intensity including the full ...
J. S. Henzing +2 more
doaj
Embedded flexible sensing technologies advance underwater soft robotics, yet most systems still suffer from hysteresis and limited perceptiveness. Instead, vision‐based tactile sensors provide reliable and rapid feedback essential for complex underwater tasks.
Qiyi Zhang +5 more
wiley +1 more source
Dynamic Bidirectional Feature Enhancement Network for Thin Cloud Removal in Remote Sensing Images
Existing thin cloud removal methods primarily rely on generative paradigms or discriminative paradigms. Generative paradigms often suffer from training instability, while discriminative paradigms exhibit insufficient feature representation, and their ...
Yu Wang, Hao Chen, Ye Zhang, Guozheng Li
doaj +1 more source
Cloud removal from optical remote sensing images
Optical remote sensing images used for Earth surface observations are constantly contaminated by cloud cover. Clouds dynamically affect the applications of optical data and increase the difficulty of image analysis. Therefore, cloud is considered as one of the sources of noise in optical image data, and its detection and removal need to be operated as ...
openaire +2 more sources
A miniaturized soft optical sensor that uses thin film color tuning enables real‐time 3D shape‐sensing from a single red–green–blue (RGB) signal. When integrated into a soft robot, it enables closed‐loop control and autonomous navigation in a phantom lung environment without the need for onboard electronics, achieving sub‐millimeter accuracy through ...
Frank Juliá Wise +6 more
wiley +1 more source

