Finding Contents or People

Spatial analysis of hyperspectral images for detecting adulteration levels in bon-sorkh (Allium jesdianum L.) seeds: Application of voting classifiers
Spatial analysis of hyperspectral images for detecting adulteration levels in bon-sorkh (Allium jesdianum L.) seeds: Application of voting classifiers
Spatial analysis of hyperspectral images for detecting adulteration levels in bon-sorkh (Allium jesdianum L.) seeds: Application of voting classifiers
Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: a comparison of machine learning tools and feature selection approaches
Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: a comparison of machine learning tools and feature selection approaches
Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: a comparison of machine learning tools and feature selection approaches
Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: a comparison of machine learning tools and feature selection approaches
Supervised deep learning for content-aware image retargeting with Fourier Convolutions
Performance Analysis of Iterative Methods in Microwave Imaging With Various Regularization Techniques
Forest edge encroachment by rural orchards shifts bird communities in favor of understory birds: Forest birds as indicators of landscape changes in agroecosystems
A Fluorescent Furan-based Probe with Protected Functional Groups for Highly Selective and Non-Toxic Imaging of HT-29 Cancer Cells and 4T1 Tumors
Fertility detection of unincubated chicken eggs by hyperspectral transmission imaging in the Vis-SWNIR region
Fertility detection of unincubated chicken eggs by hyperspectral transmission imaging in the Vis-SWNIR region
Fertility detection of unincubated chicken eggs by hyperspectral transmission imaging in the Vis-SWNIR region
Dynamic-Pix2Pix: Medical image segmentation by injecting noise to cGAN for modeling input and target domain joint distributions with limited training data