Results 131 to 140 of about 12,268,087 (190)

Correlated Decision Fusion Accompanied with Quality Information on a Multi-Band Pixel Basis for Land Cover Classification. [PDF]

J Imaging
Papadopoulos S, Koukiou G, Anastassopoulos V.   +2 more
europepmc   +1 more source

Robust feature selection for cancer microarray data using a hybrid mRMR and Binary Lion Optimization Algorithm. [PDF]

Sci Rep
Sahu B, Panigrahi A, Pati A, Madhavi BK, Mishra J, Budhathoki RK, Mallik S.   +6 more
europepmc   +1 more source

Applying Convolutional Neural Network to Predict Soil Erosion: A Case Study of Coastal Areas. [PDF]

Int J Environ Res Public Health, 2023
Liu C, Li H, Xu J, Gao W, Shen X, Miao S.   +5 more
europepmc   +1 more source

Remote sensing of savanna woody species diversity: A systematic review of data types and assessment methods. [PDF]

PLoS One, 2022
Fundisi E, Tesfamichael SG, Ahmed F.
europepmc   +1 more source

Research progress on multimodal data fusion in forest resource monitoring. [PDF]

Front Plant Sci
Wang M, Zhang Q, Liu X, Zhang J, Yu F, Zhang X, Zhao R.   +6 more
europepmc   +1 more source

CV-EEGNet: A Compact Complex-Valued Convolutional Network for End-to-End EEG-Based Emotion Recognition. [PDF]

Sensors (Basel)
Wang W, Yang D, Yang Y, Xie Y, Liu X, Yu Y, Shi K.   +6 more
europepmc   +1 more source

Satellite-based oil spill detection using an explainable ViR-SC hybrid deep learning ensemble for improved accuracy and transparency. [PDF]

Sci Rep
Murugan JS, Ramkumar K, Kshirsagar PR, Tak TK.   +3 more
europepmc   +1 more source

A Novel Change Detection Method Based on Statistical Distribution Characteristics Using Multi-Temporal PolSAR Data. [PDF]

Sensors (Basel), 2020
Zhao J, Chang Y, Yang J, Niu Y, Lu Z, Li P.   +5 more
europepmc   +1 more source

Deep Learning-Based Fusion of Optical, Radar, and LiDAR Data for Advancing Land Monitoring. [PDF]

Sensors (Basel)
Li Y, Xiao X.
europepmc   +1 more source

PolSAR image classification with Binary Partition Tree

, 2017
The objective of this project is to study new techniques in the use of Binary Partition Tree to improve the classification of objects in PolSAR images. Different techniques will be developed and the results will be compared with the state of the art. Finally, some conclusions are presented and some possible lines of future work are discussed.
openaire   +1 more source