Results 121 to 130 of about 91,296 (293)

Harmonizing ground and UAV hyperspectral data: A novel spectral correction method for maximizing estimation models and datasets of ground hyperspectral

Smart Agricultural Technology
The accurate and effective monitoring of rice nitrogen status using hyperspectral datasets and estimation models is important for precision agriculture and intelligent breeding.
Zhonglin Wang, Pengxin Deng, Kairui Chen, Ying Xiong, Feng Yang, Cheng Wang, Zhixin Li, Biao Li, Yongjian Sun, Zongkui Chen, Zhiyuan Yang, Jun Ma   +11 more
doaj   +1 more source

Assessing plant water status: Part 2 – Non‐destructive and remote sensing approaches

Journal of the Science of Food and Agriculture, EarlyView.
Abstract Precise, real time and non‐destructive assessment of plant water status is important for advancing plant physiological understanding, optimizing water usage, improving crop resilience and supporting precision agriculture in the face of increasingly variable climatic conditions.
Naila Farooq, Bo Zhang, Bastian Leander Franzisky, Tasawer Abbas, Jochen Taiber, Martin Koch, Ian C Dodd, Christoph‐Martin Geilfus   +7 more
wiley   +1 more source

Image‐based and biochemical multimodal phenotyping for explainable classification of chia (Salvia hispanica L.) genotypes

Journal of the Science of Food and Agriculture, EarlyView.
Abstract BACKGROUND This study developed an explainable machine learning framework integrating morphological, color, and biochemical characteristics for classifying chia (Salvia hispanica L.) genotypes. A dataset was assembled from 1200 seed images spanning four genotypes, from which 17 morphological and color features were extracted.
Sevim Akcura, Irem Poyraz, Beyza Ciftci, Mahmut Kaplan   +3 more
wiley   +1 more source

Artificial Intelligence in Dermatology: Current Applications and Future Directions

JEADV Clinical Practice, EarlyView.
This scoping review of 56 studies maps AI applications in dermatology. Image‐based classification for skin cancer detection dominates (48%), followed by clinical decision support (21%), teledermatology triage (11%), and predictive analytics (11%). While deep learning algorithms demonstrate diagnostic performance comparable to clinicians in controlled ...
Sofía Pérez‐Lalinde, Francisco Flores   +1 more
wiley   +1 more source

Two-Orientations Finite Markov Real-Time Local Anomaly Detection via Pixel-by-Pixel Processing for Hyperspectral Imagery

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Real-time local anomaly detection needs to be performed simultaneously with hyperspectral image acquisition. However, the discussion on the scope of using existing data, mainly focuses on line-by-line data acquisition methods and does not address pixel ...
Shihui Liu, Meiping Song
doaj   +1 more source

Correlation Hyperspectral Imaging

Physical Review Letters
Hyperspectral imaging aims at providing information on both the spatial and the spectral distribution of light, with high resolution. However, state-of-the-art protocols are characterized by an intrinsic trade-off imposing to sacrifice either resolution or image acquisition speed.
Gianlorenzo Massaro, Francesco V. Pepe, Milena D’Angelo   +2 more
openaire   +4 more sources

Optimizing Soil Organic Matter Estimation Through Multi‐Factor Zoning and Tree‐Based Automated Learning

Land Degradation &Development, EarlyView.
ABSTRACT Soil organic matter (SOM) is a key indicator of land degradation and soil functioning. It plays an essential role in nutrient cycling, soil structure, and long‐term agroecosystem resilience. The variations of surface cover, soil moisture and soil texture heterogeneity will affect the accuracy of SOM remote sensing mapping. This study developed
Xuzhou Qu, Meiyan Shu, Huiming Song, Xiaohe Gu, Jingping Zhou, Qian Sun, Baoyuan Zhang, Menglei Dai, Chunjiang Zhao   +8 more
wiley   +1 more source

Models and Methods for Automated Background Density Estimation in Hyperspectral Anomaly Detection [PDF]

, 2012
Detecting targets with unknown spectral signatures in hyperspectral imagery has been proven to be a topic of great interest in several applications. Because no knowledge about the targets of interest is assumed, this task is performed by searching the ...
VERACINI, TIZIANA
core  

A novel approach to estimate non‐algal particle absorption for improved retrieval of pigment concentrations in coastal waters

Limnology and Oceanography: Methods, EarlyView.
Abstract Phytoplankton play a central role in ocean biogeochemistry and understanding their composition and variability is critical for monitoring marine ecosystem dynamics. Continuous spectrophotometric measurements (using a Seabird Sci. AC‐S) along ship tracks enable high‐resolution measurements of particle spectral absorption (apλ$$ {a}_p\left ...
Margherita Costanzo, Vittorio E. Brando, Emmanuel Boss, Alison Chase, David Doxaran   +4 more
wiley   +1 more source

Airborne hyperspectral skydome: the new dimension of hyperspectral sensing

A new concept of hyperspectral sensor is presented. Novel design of hyperspectral skydome allows retrieval of atmospheric constituents and properties from snapshot of direct and diffuse components of spectral solar radiation, regardless of aircraft ...
Choi, Kyu Young, Milton, Edward J.
core   +1 more source