Results 51 to 60 of about 270,656 (363)
AlgorithmsThis paper describes the design, implementation, and usage of a Python package called Hyperspectral Python (HypPy). Proprietary software for processing hyperspectral images is expensive, and tools developed using these packages cannot be freely distributed.
Wim Bakker +5 more
openaire +3 more sources
En-Decoded Index Guided Edge Refinement Network for Change Detection of Remote Sensing Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingChange detection (CD) aims to analyze pairs of remote sensing images (RSIs) that are captured at different times to identify valuable information regarding changes in land features, which plays a crucial role in the fields of urban planning ...
Chunyan Yu +4 more
doaj +1 more source
Adaptive band selection snapshot multispectral imaging in the VIS/NIR domain
, 2010 Hyperspectral imaging has proven its efficiency for target detection applications but the acquisition mode and the data rate are major issues when dealing with real-time detection applications.
Ferrec, Yann +5 more
core +1 more source
Detection of multi-tomato leaf diseases (late blight, target and bacterial spots) in different stages by using a spectral-based sensor. [PDF]
, 2018 Several diseases have threatened tomato production in Florida, resulting in large losses, especially in fresh markets. In this study, a high-resolution portable spectral sensor was used to investigate the feasibility of detecting multi-diseased tomato ...
de Castro, Ana Isabel +4 more
core +2 more sources
IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingHyperspectral remote sensing technology in wetland precise mapping plays a crucial role in ecological monitoring. Currently, hyperspectral image (HSI) wetland mapping achieves remarkable progress with the development of deep learning (DL) technology ...
Chunyan Yu +6 more
doaj +1 more source
International Journal of Applied Earth Observations and Geoinformation, 2023 Wildfires frequently occur around the world, which seriously threaten the ecology, environment, economic development, even human safety. In this work, we propose a novel framework for near-real-time and early-stage wildfire detection using Himawari-8 ...
Qiang Zhang +4 more
doaj +1 more source
Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review
Italian National Conference on Sensors, 2022 The development of hyperspectral remote sensing equipment, in recent years, has provided plant protection professionals with a new mechanism for assessing the phytosanitary state of crops.
A. Terentev +3 more
semanticscholar +1 more source
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Compressive sensing (CS) has received considerable interest in hyperspectral sensing. Recent articles have also exploited the benefits of CS in hyperspectral image classification (HSIC) in the compressively sensed band domain (CSBD).
C. J. Della Porta, Chein-I Chang
doaj +1 more source
Distributed Unmixing of Hyperspectral Data With Sparsity Constraint
, 2017 Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in
Khoshsokhan, Sara +2 more
core +2 more sources
Deep learning in remote sensing: a review [PDF]
, 2017 Standing at the paradigm shift towards data-intensive science, machine learning techniques are becoming increasingly important. In particular, as a major breakthrough in the field, deep learning has proven as an extremely powerful tool in many fields ...
Fraundorfer, Friedrich +6 more
core +4 more sources