Results 41 to 50 of about 112,589 (145)

Hybrid continuum–molecular modelling of multiscale internal gas flows [PDF]

, 2013
We develop and apply an efficient multiscale method for simulating a large class of low-speed internal rarefied gas flows. The method is an extension of the hybrid atomistic–continuum approach proposed by Borg et al.
Reese, Jason M., Patronis, Alexander, Borg, Matthew K., Lockerby, Duncan A.   +3 more
core   +1 more source

Multiscale Superpixel-Guided Weighted Graph Convolutional Network for Polarimetric SAR Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Polarimetric synthetic aperture radar (PolSAR) has attracted more attentions because of its excellent observation ability, and PolSAR image classification has become one of the significant tasks in remote sensing interpretation.
Ru Wang, Yinju Nie, Jie Geng
doaj   +1 more source

Smart Brain Tumor Segmentation and Classification Using Inception ResNet‐V2 and Eagle Eye Vision in IoMT

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
Brain tumors develop due to the unregulated proliferation of nerve tissues. Nonetheless, despite progress in deep learning models for medical image analysis, the precise segmentation of tumor patches and categorization of tumor types remain unresolved.
A. Ashwini, Emmanvel Raj M. Chirchi, V. Sheeja Kumari, P. Gururama Senthilvel, Frie Ayalew, Pramita Mishra   +5 more
wiley   +1 more source

Hyperspectral Classification via Superpixel Kernel Learning-Based Low Rank Representation

Remote Sensing, 2018
High dimensional image classification is a fundamental technique for information retrieval from hyperspectral remote sensing data. However, data quality is readily affected by the atmosphere and noise in the imaging process, which makes it difficult to ...
Tianming Zhan, Le Sun, Yang Xu, Guowei Yang, Yan Zhang, Zebin Wu   +5 more
doaj   +1 more source

Multiscale Adaptive Convolution for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Convolutional neural network (CNN) is widely used in hyperspectral image (HSI) classification owing to their advantages of spatial-spectral features capture capability and learning depth features as well as their structural flexibility. Nevertheless, the
Qi Ren, Bing Tu, Qianming Li, Wangquan He, Yishu Peng   +4 more
doaj   +1 more source

Trees Outside Forests (TOFs): A Global Review of Methodological Advances, Limitations, and Framework Innovations

International Journal of Forestry Research, Volume 2026, Issue 1, 2026.
Trees outside forests (TOFs) represent an important natural and anthropogenic resource that contributes significantly to biodiversity conservation, climate resilience, and the protection of forest genetic resources (FGRs). Despite their ecological and socioeconomic importance, TOFs are increasingly declining due to land‐use changes, urbanization ...
Aman Dabral, Pawan Kumar Thakur, Maneesh S. Bhandari, Vishal Johar, Vinita Bisht, Shailesh Pandey, Rama Kant, Rajendra K. Meena, Himanshu Saini, Poulami Jha   +9 more
wiley   +1 more source

Multiscale Geometric Integration of Deterministic and Stochastic Systems [PDF]

, 2011
In order to accelerate computations and improve long time accuracy of numerical simulations, this thesis develops multiscale geometric integrators. For general multiscale stiff ODEs, SDEs, and PDEs, FLow AVeraging integratORs (FLAVORs) have been ...
Tao, Molei
core   +1 more source

Dual-Scale Pixel Aggregation Transformer for Change Detection in Multitemporal Remote Sensing Images

Remote Sensing
Transformers have recently been applied to change detection (CD) of multitemporal remote sensing images because of their ability to model global information.
Kai Zhang, Ziqing Wan, Xue Zhao, Feng Zhang, Ke Liu, Jiande Sun   +5 more
doaj   +1 more source

Multiclass Fruit Disease and Maturity Classification Using Hybrid Deep Neural and Transformer Models With Explainable AI Techniques

International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
The principal aim of this research work is to develop an efficient and explainable deep learning (DL) framework for the classification of fruit diseases. Timely and accurate detection of diseases in plants is essential in order to reduce the loss of crops and high‐quality yields.
Ranjith Kumar Anandan, Saravanan Srinivasan, A. Prathik, Jitender Tanwar, Sandeep Kumar Mathivanan, Usha Moorthy   +5 more
wiley   +1 more source

MS-ASLPEP: An Automated Sample Purification Framework for SAR Land Cover Classification Based on Hierarchical Multiscale Superpixels

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Automated and high-precision land cover classification (LCC) using synthetic aperture radar (SAR) is crucial for environmental monitoring, while its advancement has been constrained by the time-consuming and labor-intensive acquisition of sufficient and ...
Yabo Huang, Yujia Zhao, Lin Wu, JianHui Zhao, Qian Chen, Ning Li   +5 more
doaj   +1 more source