Efficient extraction of deep image features using convolutional neural network (CNN) for applications in detecting and analysing complex food matrices
Background The development of techniques and methods for rapidly and reliably detecting
and analysing food quality and safety products is of significance for the food industry …
and analysing food quality and safety products is of significance for the food industry …
Integration of hyperspectral imaging and autoencoders: Benefits, applications, hyperparameter tunning and challenges
Hyperspectral imaging (HSI) is a powerful tool that can capture and analyze a range of
spectral bands, providing unparalleled levels of precision and accuracy in data analysis …
spectral bands, providing unparalleled levels of precision and accuracy in data analysis …
Hyperspectral image classification—Traditional to deep models: A survey for future prospects
Hyperspectral imaging (HSI) has been extensively utilized in many real-life applications
because it benefits from the detailed spectral information contained in each pixel. Notably …
because it benefits from the detailed spectral information contained in each pixel. Notably …
The new hyperspectral satellite PRISMA: Imagery for forest types discrimination
Different forest types based on different tree species composition may have similar spectral
signatures if observed with traditional multispectral satellite sensors. Hyperspectral imagery …
signatures if observed with traditional multispectral satellite sensors. Hyperspectral imagery …
A comprehensive study of feature extraction techniques for plant leaf disease detection
Agriculture has been the most primary source of the livelihood of man for thousands of
years. Even today, it provides subsistence to about 50% of the world population. Plant …
years. Even today, it provides subsistence to about 50% of the world population. Plant …
Few-shot hyperspectral image classification with self-supervised learning
Recently, few-shot learning (FSL) has been introduced for hyperspectral image (HSI)
classification with few labeled samples. However, existing FSL-based HSI classification …
classification with few labeled samples. However, existing FSL-based HSI classification …
Multiple vision architectures-based hybrid network for hyperspectral image classification
F Zhao, J Zhang, Z Meng, H Liu, Z Chang… - Expert Systems with …, 2023 - Elsevier
More recently, vision transformer (ViT) has shown competitive performance with
convolutional neural network (CNN) on computer vision tasks, which provided more …
convolutional neural network (CNN) on computer vision tasks, which provided more …
Spatio-temporal sequence prediction of CO2 flooding and sequestration potential under geological and engineering uncertainties
CO 2 injection for subsurface hydrocarbon development not only enhances oil and gas
recovery but also enables CO 2 sequestration in the subsurface. It is essential to develop …
recovery but also enables CO 2 sequestration in the subsurface. It is essential to develop …
Comparison of various deep convolutional neural network models to discriminate apple leaf diseases using transfer learning
P Pradhan, B Kumar, S Mohan - Journal of Plant Diseases and Protection, 2022 - Springer
Plant diseases are the major factor behind production loss in agriculture. The traditional
manual methods for disease detection in plants involve expert knowledge that may be …
manual methods for disease detection in plants involve expert knowledge that may be …
Coupled retrieval of heavy metal nickel concentration in agricultural soil from spaceborne hyperspectral imagery
Y Sun, S Chen, X Dai, D Li, H Jiang, K Jia - Journal of Hazardous Materials, 2023 - Elsevier
Widespread soil contamination endangers public health and undermines global attempts to
achieve the United Nations Sustainable Development Goals. Due to the lack of relevant …
achieve the United Nations Sustainable Development Goals. Due to the lack of relevant …