Results 81 to 90 of about 4,082 (191)

Advancing Canning Quality in Common Beans: An Integrated Farm‐to‐Can Framework Combining Breeding, Processing, and Artificial Intelligence

Legume Science, Volume 8, Issue 2, June 2026.
ABSTRACT Common beans (Phaseolus vulgaris L.) are essential raw material for the canning industry. This article reviews recent advances in assessing canning quality and the integration of artificial intelligence (AI) into breeding methodologies aimed at developing genotypes with superior yield and canning‐quality traits.
Arash Ghaitaranpour, Biniam Kebede, Mohsen Yoosefzadeh‐Najafabadi   +2 more
wiley   +1 more source

WTL-I: Mutual Information-Based Wavelet Transform Learning for Hyperspectral Imaging

Frontiers in Signal Processing, 2022
Hyperspectral imaging (HSI) is useful in many applications, including healthcare, geosciences, and remote surveillance. In general, the HSI data set is large.
Shiv Gehlot, Naushad Ansari, Anubha Gupta   +2 more
doaj   +1 more source

Assessing Moisture Content of Coolstored Blueberries During Water Loss Scenarios Using Hyperspectral Imaging

New Zealand Journal of Crop and Horticultural Science, Volume 54, Issue 2, June 2026.
Water loss is a key factor affecting the postharvest quality and shelf life of blueberries, and storage conditions (humidity and time) play an important role in regulating water retention capacity of stored berries. This study aims to explore the variation of moisture content (MC) in blueberries under different storage humidity and storage time ...
RunKai Wang, Craig McGill, Eduardo Sandoval, Mo Li   +3 more
wiley   +1 more source

Hyperspectral Image Classification Based on Sparse Superpixel Graph

, 2021
Hyperspectral image (HSI) classification is one of the major problems in the field of remote sensing. Particularly, graph-based HSI classification is a promising topic and has received increasing attention in recent years.
Yifei Zhao, Fengqin Yan
core   +1 more source

Toward Content-Based Hyperspectral Remote Sensing Image Retrieval (CB-HRSIR): A Preliminary Study Based on Spectral Sensitivity Functions

Remote Sensing, 2019
With the emergence of huge volumes of high-resolution Hyperspectral Images (HSI) produced by different types of imaging sensors, analyzing and retrieving these images require effective image description and quantification techniques.
Olfa Ben-Ahmed, Thierry Urruty, Noël Richard, Christine Fernandez-Maloigne   +3 more
doaj   +1 more source

Hyperspectral and Infrared Image Collaborative Classification Based on Morphology Feature Extraction

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
With the development of sensor technology, fusion of multiple remote sensors has aroused wide attention in the earth observation area. In this article, we propose to integrate the complementary information of hyperspectral image (HSI) and infrared image (
Dandan Cao, Mengmeng Zhang, Wei Li, Qiong Ran   +3 more
doaj   +1 more source

A Comprehensive Review of Traditional and Machine Learning‐Assisted Diffuse Optical Spectroscopy and Imaging Techniques for Dermatological Applications

Advanced Photonics Research, Volume 7, Issue 5, May 2026.
This review critically examines clinical studies on both conventional and machine learning (ML)‐integrated diffuse optical spectroscopy and imaging methods for dermatological applications, with a primary focus on the past decade and inclusion of earlier foundational work where appropriate.
Iftak Hussain, Li Xiuting, Randall Ang Jie, Keertana Vinod Ram, Mark Teo Ju Teng, Valerie Xinhui Teo, Malini Olivo, U. S. Dinish   +7 more
wiley   +1 more source

Automatic live and dead cell classification via hyperspectral imaging

, 2019
Classification of live and dead human ovarian cancer cells (SKOV3) is an important task in biomedicine research. Fluorescence is the most common technique to distinguish live and dead cells.
Nguyen, Nam-Trung, Nguyen, NT, Chun-Xia Zhao, Gao, Y, Ho, Benjamin, Jun Zhou, Zhou, Jun, Tan, Say Hwa, Wang, Haofei, Zhao, Chun-Xia, Nam-Trung Nguyen, He Chen, Chen, He, Yongsheng Gao, Zhao, CX, Ho, B, Wang, H, Say Hwa Tan, Haofei Wang, Zhou, J, Benjamin Ho, Chen, H, Tan, SH, Gao, Yongsheng   +23 more
core   +1 more source

A Dual-Path Small Convolution Network for Hyperspectral Image Classification

, 2021
Convolutional neural network (CNN) has shown excellent performance in hyperspectral image (HSI) classification. However, the structure of the CNN models is complex, requiring many training parameters and floating-point operations (FLOPs).
Jay Lee, Lanxue Dang, Xianyu Zuo, Peidong Pang, Yang Liu   +4 more
core   +1 more source

Spectral–spatial mamba adversarial defense network for hyperspectral image classification

International Journal of Digital Earth
Deep learning models have obtained great success in hyperspectral image classification tasks. Nevertheless, they are usually vulnerable to adversarial attacks. Some existing works have been made to defend against adversarial attacks in HSI classification.
Zhongqiang Zhang, Ye Wang, Dahua Gao, Haoyong Li, Guangming Shi   +4 more
doaj   +1 more source