Results 41 to 50 of about 25,036,571 (294)
Temporal and Spatial Denoising of Depth Maps
Sensors, 2015 This work presents a procedure for refining depth maps acquired using RGB-D (depth) cameras. With numerous new structured-light RGB-D cameras, acquiring high-resolution depth maps has become easy. However, there are problems such as undesired occlusion,
Bor-Shing Lin +4 more
doaj +1 more source
GrapesNet: Indian RGB & RGB-D vineyard image datasets for deep learning applications
Data in Brief, 2023 In most of the countries, grapes are considered as a cash crop. Currently huge research is going on in development of automated grape harvesting systems.
Dhanashree K. Barbole, Parul M. Jadhav
doaj +1 more source
Investigating 2-D and 3-D Proximal Remote Sensing Techniques for Vineyard Yield Estimation
Sensors, 2019 Vineyard yield estimation provides the winegrower with insightful information regarding the expected yield, facilitating managerial decisions to achieve maximum quantity and quality and assisting the winery with logistics.
Chris Hacking +3 more
doaj +1 more source
Multi-scale fusion for RGB-D indoor semantic segmentation
Scientific Reports, 2022 In computer vision, convolution and pooling operations tend to lose high-frequency information, and the contour details will also disappear with the deepening of the network, especially in image semantic segmentation.
Shiyi Jiang +3 more
doaj +1 more source
, 2021 (a) RGB image outlining dead trees. (b) Image derived from new NDSI to differentiate dead trees after thresholding (14 October 2020) (c) NDVI image after thresholding (d) PCA NDVI image after thresholding.
Shara Ahmed (11708088) +4 more
core +1 more source
Interactive Multi-label Segmentation of RGB-D Images [PDF]
, 2015 We propose a novel interactive multi-label RGB-D image segmentation method by extending spatially varying color distributions [14] to additionally utilize depth information in two different ways. On the one hand, we consider the depth image as an additional data channel.
Julia Diebold +4 more
openaire +2 more sources
All in One: RGB, RGB-D, and RGB-T Salient Object Detection [PDF]
, 2023 Salient object detection (SOD) aims to identify the most attractive objects within an image. Depending on the type of data being detected, SOD can be categorized into various forms, including RGB, RGB-D (Depth), RGB-T (Thermal) and light field SOD ...
Zhao, Zhongqiu +3 more
core
, 2021 For silver birch and oak trees (d) RGB image (e) image derived from (PC1-PC2)/(PC1+PC2) (f) image derived from (PC1-PC3)/(PC1+PC3).
Shara Ahmed (11708088) +4 more
core +1 more source
Advanced Engineering Materials, EarlyView.Low‐cycle fatigue damage in Mn–Mo–Ni reactor pressure vessel steel is examined using a combined electron backscatter diffraction and positron annihilation lifetime spectroscopy approach. The study correlates texture evolution, dislocation substructure development, and vacancy‐type defect formation across uniform, necked, and fracture regions, providing
Apu Sarkar +2 more
wiley +1 more source
RGB-D SLAM Based on Extended Bundle Adjustment with 2D and 3D Information
Sensors, 2016 In the study of SLAM problem using an RGB-D camera, depth information and visual information as two types of primary measurement data are rarely tightly coupled during refinement of camera pose estimation. In this paper, a new method of RGB-D camera SLAM
Kaichang Di +4 more
doaj +1 more source