Results 161 to 170 of about 49,813 (252)

AI‐Enabled Imaging for Pathogen Detection Under Stress Conditions: A Systematic Review

Comprehensive Reviews in Food Science and Food Safety, Volume 25, Issue 3, May 2026.
ABSTRACT Advances in pathogen detection that incorporate artificial intelligence (AI) may capture microbial signals under challenging environmental conditions that traditional methods miss. This systematic review evaluates the application, performance, and methodological characteristics of AI‐enabled imaging for pathogen detection, including its impact
MeiLi Papa, Gillian Kuehnle, Yoo Jung (Erika) Oh, Jiyoon Yi   +3 more
wiley   +1 more source

SGFNet: Redundancy-Reduced Spectral-Spatial Fusion Network for Hyperspectral Image Classification. [PDF]

Entropy (Basel)
Wang B, Cao C, Kong D.
europepmc   +1 more source

Spectral Characterization of the Life Stages and Physiological Responses of Diatraea saccharalis Fabricius (Lepidoptera: Crambidae) Larvae Parasitized by Cotesia flavipes Cameron (Hymenoptera: Braconidae)

Entomologia Experimentalis et Applicata, Volume 174, Issue 5, Page 436-452, May 2026.
Hyperspectral proximal sensing was used to characterize the life stages and physiological responses of Diatraea saccharalis and to detect parasitism by Cotesia flavipes. Distinct spectral signatures differentiated eggs, larval instars, pupae, and adults, as well as live, dead, and parasitized larvae.
Souradji I. Bachirou, David L. Rosalen, Sergio A. De Bortoli, Pedro G. Peixoto   +3 more
wiley   +1 more source

Semantic-Aware Co-Parallel Network for Cross-Scene Hyperspectral Image Classification. [PDF]

Sensors (Basel)
Li X, Jin C, Tang Y, Xing K, Yu X.
europepmc   +1 more source

Retracted: A 3D-2D Convolutional Neural Network and Transfer Learning for Hyperspectral Image Classification. [PDF]

Comput Intell Neurosci, 2023
Intelligence And Neuroscience C.
europepmc   +1 more source

Beyond high‐throughput: leveraging plant phenotyping to improve understanding and prediction of plant growth through process‐based models

New Phytologist, Volume 250, Issue 3, Page 1468-1482, May 2026.
Summary The last decade has marked a period of rapid innovation in high‐throughput phenotyping (HTP) of plants. This includes the establishment of robotic phenotyping infrastructure, development of new sensors, and improvements in computation for downstream analysis.
To‐Chia Ting, D. Scott Mackay, Jinha Jung, Matthew P. Reynolds, Yang Yang, Diane R. Wang   +5 more
wiley   +1 more source

Tri branch attention enhanced 3DUNet for remote sensing based hyperspectral image classification. [PDF]

Sci Rep
Ashraf M, Abbas T, Iqbal S, Sayyed A, Asghar MN, Alaulamie A.   +5 more
europepmc   +1 more source

Mutual Information-Driven Feature Reduction for Hyperspectral Image Classification. [PDF]

Sensors (Basel), 2023
Islam MR, Ahmed B, Hossain MA, Uddin MP.
europepmc   +1 more source

Assessing functional diversity and composition using multispectral images in Atlantic Forest restoration sites

Restoration Ecology, Volume 34, Issue 4, May 2026.
Abstract Introduction By focusing on the specific functional traits of species, we can better understand how ecosystems function and respond to environmental change. However, field measurements of functional traits can be time‐consuming and costly, whereas remote sensing data can serve as viable alternatives for studying biodiversity at larger scales ...
Júlia Ayres de Oliveira, Ângelo Mantovani Amorim de Freitas Oliveira, André Quintão de Almeida, Catherine Torres de Almeida, Eric Bastos Gorgens, Vinicius Nunes Henrique Silva, Luiz Fernando Duarte de Moraes, Gustavo Bastos Lyra, Jerônimo Boelsums Barreto Sansevero   +8 more
wiley   +1 more source

Progressive multi-scale multi-attention fusion for hyperspectral image classification. [PDF]

Sci Rep
Wang H, Quan S, Liu J, Xiao H, Peng Y, Wang Z, Li H.   +6 more
europepmc   +1 more source