Computer vision and deep learning techniques for pedestrian detection and tracking: A survey

A Brunetti, D Buongiorno, GF Trotta, V Bevilacqua - Neurocomputing, 2018 - Elsevier
Pedestrian detection and tracking have become an important field in the computer vision
research area. This growing interest, started in the last decades, might be explained by the …

Biomolecular and bioanalytical applications of infrared spectroscopy–A review

KB Beć, J Grabska, CW Huck - Analytica chimica acta, 2020 - Elsevier
Infrared (IR; or mid-infrared, MIR; 4000-400 cm− 1; 2500–25,000 nm) spectroscopy has
become one of the most powerful and versatile tools at the disposal of modern bioscience …

Deep supervised learning for hyperspectral data classification through convolutional neural networks

K Makantasis, K Karantzalos… - … and remote sensing …, 2015 - ieeexplore.ieee.org
Spectral observations along the spectrum in many narrow spectral bands through
hyperspectral imaging provides valuable information towards material and object …

An effective evaluation tool for hyperspectral target detection: 3D receiver operating characteristic curve analysis

CI Chang - IEEE Transactions on Geoscience and Remote …, 2020 - ieeexplore.ieee.org
Receiver operating characteristic (ROC) analysis is performed by a curve, called ROC curve,
plotted based on detection probability, PD, versus false alarm probability, PF, and has been …

Hyperspectral satellites, evolution, and development history

SE Qian - IEEE Journal of Selected Topics in Applied Earth …, 2021 - ieeexplore.ieee.org
Hyperspectral imaging has been emerged as a new generation of technology for earth
observation and space exploration since the beginning of this millennium and widely used …

Target detection with unconstrained linear mixture model and hierarchical denoising autoencoder in hyperspectral imagery

Y Li, Y Shi, K Wang, B **, J Li… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Hyperspectral imagery with very high spectral resolution provides a new insight for subtle
nuances identification of similar substances. However, hyperspectral target detection faces …

Effective anomaly space for hyperspectral anomaly detection

CI Chang - IEEE Transactions on Geoscience and Remote …, 2022 - ieeexplore.ieee.org
Due to unavailability of prior knowledge about anomalies, background suppression (BS) is a
crucial factor in anomaly detection (AD) evaluation. The difficulty in dealing with BS arises …

Hyperspectral image reconstruction by deep convolutional neural network for classification

Y Li, W **e, H Li - Pattern Recognition, 2017 - Elsevier
Spatial features of hyperspectral imagery (HSI) have gained an increasing attention in the
latest years. Considering deep convolutional neural network (CNN) can extract a hierarchy …

A review of the medical hyperspectral imaging systems and unmixing algorithms' in biological tissues

A ul Rehman, SA Qureshi - Photodiagnosis and Photodynamic Therapy, 2021 - Elsevier
Hyperspectral fluorescence imaging (HFI) is a well-known technique in the medical research
field and is considered a non-invasive tool for tissue diagnosis. This review article gives a …

Early detection and quantification of Verticillium wilt in olive using hyperspectral and thermal imagery over large areas

R Calderón, JA Navas-Cortés, PJ Zarco-Tejada - Remote Sensing, 2015 - mdpi.com
Automatic methods for an early detection of plant diseases (ie, visible symptoms at early
stages of disease development) using remote sensing are critical for precision crop …