Results 261 to 270 of about 57,062 (333)
ATSFCNN: a novel attention-based triple-stream fused CNN model for hyperspectral image classification [PDF]
Jizhen CAI +2 more
openalex +1 more source
ABSTRACT Milk and milk powder are central to global nutrition, yet remain vulnerable to adulteration and contamination. Adulteration using water, urea, ammonium sulfate, thiocyanates, detergents, melamine, or compositional changes with whey and carbohydrate fillers undermines nutritional quality, reduces consumer confidence, and challenges regulatory ...
B. Sudarshan Acharya +2 more
wiley +1 more source
Unveiling the potential of diffusion model-based framework with transformer for hyperspectral image classification. [PDF]
Sigger N +4 more
europepmc +1 more source
Abstract Virtual laser scanning (VLS) is an established and valuable research tool in forestry and ecology, widely used to simulate labelled light detection and ranging (LiDAR) point cloud data for sensitivity analysis, model training for machine learning (ML) and method testing.
Hannah Weiser, Bernhard Höfle
wiley +1 more source
Transfer Learning-Based Hyperspectral Image Classification Using Residual Dense Connection Networks. [PDF]
Zhou H, Wang X, Xia K, Ma Y, Yuan G.
europepmc +1 more source
Triple Graph Convolutional Network for Hyperspectral Image Feature Fusion and Classification [PDF]
Maryam Imani, Daniele Cerra
openalex +1 more source
Refugia or at risk? Alpine snowbank communities in the face of climate change
We used a literature review of the alpine snowbank communities of the Presidential Range of New Hampshire, USA as an model system for applying the climate change refugia conservation cycle framework to similar imperiled systems globally. We highlight threats posed to these systems, their ability to serve as future refugia, potential management ...
Kyler B. B. Phillips +5 more
wiley +1 more source
Joint Spatial-Spectral Convolutional Neural Network Enhanced with Attention Mechanism for Optimized Hyperspectral Image Classification [PDF]
Xueqing Zhao
openalex +1 more source
Neural Networks for Space Debris Classification
ABSTRACT Significant research in the field of space domain awareness (SDA) has focused on improving AI‐driven data processing and classification tasks. Previous studies have explored the classification of orbiting man‐made object types such as satellites, rocket bodies, and debris, yet there is a noticeable gap in the literature concerning the ...
Anne Adriano +4 more
wiley +1 more source

