Results 71 to 80 of about 1,313 (183)

Hyperspectral Remote Sensing Images Feature Extraction Based on Spectral Fractional Differentiation

Remote Sensing, 2023
To extract effective features for the terrain classification of hyperspectral remote-sensing images (HRSIs), a spectral fractional-differentiation (SFD) feature of HRSIs is presented, and a criterion for selecting the fractional-differentiation order is ...
Jing Liu, Yang Li, Feng Zhao, Yi Liu
doaj   +1 more source

Hyperspectral Imaging: The Intelligent Eye to Uncover the Password of Plant Science

Modern Agriculture, Volume 3, Issue 2, December 2025.
Hyperspectral imaging (HSI) has emerged as a powerful non‐destructive technique for characterisation of the plant phenotype and physiological traits. The ongoing development of cost‐effective hardware, coupled with standardised acquisition protocols and open‐access spectral libraries, is accelerating its integration with multi‐omics approaches to ...
Jingyan Song, Haifeng Liang, Bingjie Lu, Jing Guo, Yuan Gao, Xiao Hu, Manlin Yang, Xiaofan Li, Zhenyu Wang, Yongqi Chen, Yinyin Zhang, Shen Su, Zhangyun Gao, Shijie Li, Ping Chen, Jing Wang, Wanneng Yang, Hui Feng   +17 more
wiley   +1 more source

Three‐Dimensional Full Variables Bias Correction of CMA‐GFS Analysis Field Using Spatial Convolutional Long Short‐Term Memory Network

Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 4, December 2025.
Abstract Numerical weather prediction models are essential for modern meteorological forecasting, with accuracy critically hinging on the precision of initial analysis fields. Compared to the ERA5 global reanalysis data, the analysis fields produced by the China Meteorological Administration Global Forecast System (CMA‐GFS) exhibit notable biases in ...
Haoyuan Huang, Jun Yang, Yang Han, Hao Hu, Yi‐Ning Shi, Fuzhong Weng   +5 more
wiley   +1 more source

Harnessing Deep Learning of Point Clouds for Morphology Mimicking of Universal 3D Shape‐Morphing Devices

Advanced Intelligent Systems, Volume 7, Issue 9, September 2025.
Soft robots capable of morphing into various 3D shapes are crucial for applications like human‐machine interfaces and biological manipulation. However, controlling 3D shape‐morphing robots with soft actuators remains a challenge. This work introduces a machine learning model that maps complex 3D deformations to control inputs, enabling robots to mimic ...
Jue Wang, Dhirodaatto Sarkar, Jiaqi Suo, Alex Chortos   +3 more
wiley   +1 more source

A Deep Learning‐Based Long‐Term ENSO Forecasting Model: 3D‐STransformer

Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 3, September 2025.
Abstract The El Niño‐Southern Oscillation (ENSO) significantly impacts global climate variability, causing extreme events like droughts, floods, and heatwaves. Accurate prediction of ENSO is critical for managing agriculture, water resources, disaster prevention, and economic planning.
Jie Lian, Xinjiao Wu, Sirong Huang, Zhanyuan Chang   +3 more
wiley   +1 more source

LP-3DCNN: Unveiling Local Phase in 3D Convolutional Neural Networks [PDF]

2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019
Accepted in CVPR ...
Sudhakar Kumawat, Shanmuganathan Raman
openaire   +2 more sources

Data_Sheet_2_Resting state network mapping in individuals using deep learning.zip

, 2023
IntroductionResting state functional MRI (RS-fMRI) is currently used in numerous clinical and research settings. The localization of resting state networks (RSNs) has been utilized in applications ranging from group analysis of neurodegenerative diseases
Evan M. Gordon (14394084), Ryan V. Raut (14394078), Karin L. Meeker (14394081), Ki Yun Park (9193166), Eric C. Leuthardt (7348868), Abraham Z. Snyder (8027606), John J. Lee (7972976), Beau M. Ances (8294550), Joshua S. Shimony (8027603), Patrick H. Luckett (14394075)   +9 more
core   +1 more source

Automated Assessment of Simulated Laparoscopic Surgical Performance using 3DCNN

2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
Artificial intelligence & Computer vision have the potential to improve surgical training, especially for minimally invasive surgery by analyzing intraoperative and simulation videos for training or performance improvement purposes. Among these, techniques based on deep learning have rapidly improved, from recognizing objects, instruments, and gestures,
David Power, Ihsan Ullah
openaire   +4 more sources

Accelerating Urban Flood Inundation Simulation Under Spatio‐Temporally Varying Rainstorms Using ConvLSTM Deep Learning Model

Water Resources Research, Volume 61, Issue 8, August 2025.
Abstract Urban floods induced by rainstorms can lead to severe losses of lives and property, making rapid flood prediction essential for effective disaster prevention and mitigation. However, traditional deep learning (DL) models often overlook the spatial heterogeneity of rainstorms and lack interpretability.
Yaoxing Liao, Zhaoli Wang, Haijun Yu, Weizhi Gao, Zhaoyang Zeng, Xuefang Li, Chengguang Lai   +6 more
wiley   +1 more source

Enhanced Lung Cancer Prediction via Integrated Multi‐Space Feature Adaptation, Collaborative Alignment and Disentanglement Learning

Engineering Reports, Volume 7, Issue 1, January 2025.
The research presents an enhanced lung cancer prediction model integrating AMSF‐L1ELM with Primitive Generation with Collaborative Relationship Alignment and Feature Disentanglement Learning. The model improves test accuracy, precision, recall, F1‐score, and ROC‐AUC across multiple domains in complex medical imaging data.
Abigail Kawama, Ronald Waweru Mwangi, Lawrence Nderu   +2 more
wiley   +1 more source