Results 71 to 80 of about 49,813 (252)

Multiple Feature Learning Based on Edge-Preserving Features for Hyperspectral Image Classification

IEEE Access, 2019
The classification of hyperspectral images is the basis and hotspot in the research of hyperspectral images. In this paper, a classification algorithm of hyperspectral image based on multiple edge-preserving features and multiple feature learning (MFL ...
Wei Tian, Lizhong Xu, Zhe Chen, Aiye Shi
doaj   +1 more source

Fusion of pixel-based and object-based features for classification of urban hyperspectral remote sensing data [PDF]

, 2014
Hyperspectral imagery contains a wealth of spectral and spatial information that can improve target detection and recognition performance. Typically, spectral information is inferred pixel-based, while spatial information related to texture, context and ...
Devriendt, Flore, Gautama, Sidharta, Liao, Wenzhi, Philips, Wilfried, Pizurica, Aleksandra, Vancoillie, Frieke   +5 more
core  

Archaeological Damage Assessment in Conflict Zones: Integrating Satellite Imagery and Ground Surveys in Daraa, Syria

Archaeological Prospection, EarlyView.
ABSTRACT Satellite remote sensing is among the most significant modern methodologies supporting field archaeology. In addition to its efficiency in identifying archaeological sites, remote sensing offers a safe and cost‐effective approach in conflict zones.
Amal Al Kassem, Kristen Hopper, Ismael M. Ibraheem, Andreas Maier, Mohammad Khair Nassrallah, Jürgen Richter   +5 more
wiley   +1 more source

Synergistic 2D/3D Convolutional Neural Network for Hyperspectral Image Classification

Remote Sensing, 2020
Accurate hyperspectral image classification has been an important yet challenging task for years. With the recent success of deep learning in various tasks, 2-dimensional (2D)/3-dimensional (3D) convolutional neural networks (CNNs) have been exploited to
Xiaofei Yang, Xiaofeng Zhang, Yunming Ye, Raymond Y. K. Lau, Shijian Lu, Xutao Li, Xiaohui Huang   +6 more
doaj   +1 more source

GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection

, 2019
Change detection (CD) is an important application of remote sensing, which provides timely change information about large-scale Earth surface. With the emergence of hyperspectral imagery, CD technology has been greatly promoted, as hyperspectral data ...
Du, Qian, Fellow, Fellow, IEEE, IEEE, IEEE, Li, Xuelong, Member, Senior, Wang, Qi, Yuan, Zhenghang   +9 more
core   +1 more source

Hyperspectral Image Classification with Convolutional Neural Networks [PDF]

Proceedings of the 23rd ACM international conference on Multimedia, 2015
Hyperspectral image (HSI) classification is one of the most widely used methods for scene analysis from hyperspectral imagery. In the past, many different engineered features have been proposed for the HSI classification problem. In this paper, however, we propose a feature learning approach for hyperspectral image classification based on convolutional
Slavkovikj, Viktor, Verstockt, Steven, De Neve, Wesley, Van Hoecke, Sofie, Van de Walle, Rik   +4 more
openaire   +2 more sources

Real‐time lithology identification while drilling based on drill cuttings image analysis with ensemble learning

Deep Underground Science and Engineering, EarlyView.
A lithology identification while drilling method was developed, integrating an automated cuttings sampling system, a smart drilling rig, and an ensemble learning model. Underground trials achieved 97.42% accuracy in real‐time identification of cuttings lithology and composition, enhancing hazard management and supporting unmanned drilling technology in
Kun Li, Ting Ren, Ningping Yao, Jon Roberts, Haitao Song, Zhongbei Li, Xueqiu He, Liang Zhao   +7 more
wiley   +1 more source

Graph inductive learning method for small sample classification of hyperspectral remote sensing images

European Journal of Remote Sensing, 2020
In recent years, deep learning has drawn increasing attention in the field of hyperspectral remote sensing image classification and has achieved great success.
Xibing Zuo, Xuchu Yu, Bing Liu, Pengqiang Zhang, Xiong Tan, Xiangpo Wei   +5 more
doaj   +1 more source

Segmentation-Aware Hyperspectral Image Classification

, 2019
To appear at International Geoscience and Remote Sensing Symposium (IGARSS ...
Demirel, Berkan, Ozdil, Omer, Esin, Yunus Emre, Ozturk, Safak   +3 more
openaire   +2 more sources

Toxicological Evaluation of the Undesirable Components in Processed Infant Foods Using Artificial Intelligence

Future Postharvest and Food, EarlyView.
The detection of toxins in baby food using artificial intelligence. ABSTRACT Infant foods and baby formulas are becoming increasingly popular across the globe owing to their ease of consumption and nutritional value specific to infants. Impurities may find their way into the food chain at any point from the acquisition of raw materials to final ...
Poornima Singh, Anurag Singh, Ashutosh Upadhyay, Navneet Kumar   +3 more
wiley   +1 more source