Search Results for author:
Found 8 papers, 6 papers with code
PCB-Vision: A Multiscene RGB-Hyperspectral Benchmark Dataset of Printed Circuit Boards
Addressing the critical theme of recycling electronic waste (E-waste), this contribution is dedicated to developing advanced automated data processing pipelines as a basis for decision-making and process control.
TSGAN: An Optical-to-SAR Dual Conditional GAN for Optical based SAR Temporal Shifting
We propose a novel approach, termed SAR Temporal Shifting, which inputs an optical data from the desired timestamp along with a SAR data from a different temporal point but with a consistent viewing geometry as the expected SAR data, both complemented with a change map of optical data during the intervening period.
Masking Hyperspectral Imaging Data with Pretrained Models
The presence of undesired background areas associated with potential noise and unknown spectral characteristics degrades the performance of hyperspectral data processing.
Tinto: Multisensor Benchmark for 3D Hyperspectral Point Cloud Segmentation in the Geosciences
To address these challenges, we present Tinto, a multi-sensor benchmark digital outcrop dataset designed to facilitate the development and validation of deep learning approaches for geological mapping, especially for non-structured 3D data like point clouds.
HyDe: The First Open-Source, Python-Based, GPU-Accelerated Hyperspectral Denoising Package
Furthermore, we present a method for training DNNs for denoising HSIs which are not spatially related to the training dataset, i. e., training on ground-level HSIs for denoising HSIs with other perspectives including airborne, drone-borne, and space-borne.
Unsupervised Data Fusion With Deeper Perspective: A Novel Multisensor Deep Clustering Algorithm
In this article, we propose a multisensor deep clustering (MDC) algorithm for the joint processing of multisource imaging data.
Fusion of Dual Spatial Information for Hyperspectral Image Classification
In the spatial optimization stage, a pixel-level classifier is used to obtain the class probability followed by an extended random walker-based spatial optimization technique.
Multisource and Multitemporal Data Fusion in Remote Sensing
The sharp and recent increase in the availability of data captured by different sensors combined with their considerably heterogeneous natures poses a serious challenge for the effective and efficient processing of remotely sensed data.
