Big data and machine learning with hyperspectral information in agriculture
KLM Ang, JKP Seng - IEEE Access, 2021 - ieeexplore.ieee.org
Hyperspectral and multispectral information processing systems and technologies have
demonstrated its usefulness for the improvement of agricultural productivity and practices by …
demonstrated its usefulness for the improvement of agricultural productivity and practices by …
A tutorial on distance metric learning: Mathematical foundations, algorithms, experimental analysis, prospects and challenges
Distance metric learning is a branch of machine learning that aims to learn distances from
the data, which enhances the performance of similarity-based algorithms. This tutorial …
the data, which enhances the performance of similarity-based algorithms. This tutorial …
Deep plug-and-play prior for hyperspectral image restoration
Deep-learning-based hyperspectral image (HSI) restoration methods have gained great
popularity for their remarkable performance but often demand expensive network retraining …
popularity for their remarkable performance but often demand expensive network retraining …
Enhanced drowsiness detection using deep learning: an fNIRS study
In this paper, a deep-learning-based driver-drowsiness detection for brain-computer
interface (BCI) using functional near-infrared spectroscopy (fNIRS) is investigated. The …
interface (BCI) using functional near-infrared spectroscopy (fNIRS) is investigated. The …
Malware‐SMELL: A zero‐shot learning strategy for detecting zero‐day vulnerabilities
One of the most relevant security problems is inferring whether a program has malicious
intent (malware software). Even though Antivirus is one of the most popular approaches for …
intent (malware software). Even though Antivirus is one of the most popular approaches for …
Hyperspectral image classification based on convolutional neural network and random forest
Deep learning-based methods, especially deep convolutional neural network (CNN), have
proven their powerfulness in hyperspectral image (HSI) classification. On the other hand …
proven their powerfulness in hyperspectral image (HSI) classification. On the other hand …
Advances in infrared spectroscopy combined with artificial neural network for the authentication and traceability of food
N Liang, S Sun, C Zhang, Y He… - Critical Reviews in Food …, 2022 - Taylor & Francis
The authentication and traceability of food attract more attention due to the increasing
consumer awareness regarding nutrition and health, being a new hotspot of food science …
consumer awareness regarding nutrition and health, being a new hotspot of food science …
A fast and compact hybrid CNN for hyperspectral imaging-based bloodstain classification
In forensic sciences, blood is a shred of essential evidence for reconstructing crime scenes.
Blood identification and classification may help to confirm a suspect, although several …
Blood identification and classification may help to confirm a suspect, although several …
Mixed attention network for hyperspectral image denoising
Hyperspectral image denoising is unique for the highly similar and correlated spectral
information that should be properly considered. However, existing methods show limitations …
information that should be properly considered. However, existing methods show limitations …
Fusion of geochemical and remote-sensing data for lithological mapping using random forest metric learning
Multisource geoscience data can provide significant information for mineral exploration in a
variety of ways. For example, remote-sensing images record the spectral characteristics of …
variety of ways. For example, remote-sensing images record the spectral characteristics of …