Two headed dragons: Multimodal fusion and cross modal transactions
As the field of remote sensing is evolving, we witness the accumulation of information from
several modalities, such as multispectral (MS), hyperspectral (HSI), LiDAR etc. Each of these …
several modalities, such as multispectral (MS), hyperspectral (HSI), LiDAR etc. Each of these …
[HTML][HTML] Multi-modal fusion of satellite and street-view images for urban village classification based on a dual-branch deep neural network
With the rapid urbanization process in China, numerous urban villages have been
appeared, which are surrounded by the newly-built urban blocks. Due to the high population …
appeared, which are surrounded by the newly-built urban blocks. Due to the high population …
Chatmap: Large Language Model Interaction with Cartographic Data
E Unlu - arXiv preprint arXiv:2310.01429, 2023 - arxiv.org
The swift advancement and widespread availability of foundational Large Language Models
(LLMs), complemented by robust fine-tuning methodologies, have catalyzed their adaptation …
(LLMs), complemented by robust fine-tuning methodologies, have catalyzed their adaptation …
Sensor fusion by spatial encoding for autonomous driving
Sensor fusion is critical to perception systems for task domains such as autonomous driving
and robotics. Recently, the Transformer integrated with CNN has demonstrated high …
and robotics. Recently, the Transformer integrated with CNN has demonstrated high …
Collaborating heterogeneous natural language processing tasks via federated learning
The increasing privacy concerns on personal private text data promote the development of
federated learning (FL) in recent years. However, the existing studies on applying FL in NLP …
federated learning (FL) in recent years. However, the existing studies on applying FL in NLP …
Hybrid attention-aware transformer network collaborative multiscale feature alignment for building change detection
Building change detection (BCD) is essential for urban dynamic measurement. Deep
learning has demonstrated significant potential in image processing, providing powerful …
learning has demonstrated significant potential in image processing, providing powerful …
Giobalfusion: A global attentional deep learning framework for multisensor information fusion
The paper enhances deep-neural-network-based inference in sensing applications by
introducing a lightweight attention mechanism called the global attention module for multi …
introducing a lightweight attention mechanism called the global attention module for multi …
DMNet: A network architecture using dilated convolution and multiscale mechanisms for spatiotemporal fusion of remote sensing images
W Li, X Zhang, Y Peng, M Dong - IEEE Sensors Journal, 2020 - ieeexplore.ieee.org
Since remote sensing images cannot have both high temporal resolution and high spatial
resolution, spatiotemporal fusion of remote sensing images has attracted increasing …
resolution, spatiotemporal fusion of remote sensing images has attracted increasing …
City Digital Twins: their maturity level and differentiation from 3D city models
H Masoumi, S Shirowzhan, P Eskandarpour… - Big Earth Data, 2023 - Taylor & Francis
The emerging field of City Digital Twins has advanced in recent years with the help of digital
infrastructure and technologies connected to the Internet of Things (IoT). However, the …
infrastructure and technologies connected to the Internet of Things (IoT). However, the …
DMF-net: a dual remote sensing image fusion network based on multi-scale convolutional dense connectivity with performance measure
H Guo, X Jin, Q Jiang, M Wozniak… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Pan-sharpening is a remote sensing image-processing technique whose main objective is
to generate images with high spatial and spectral resolution by combining high-spatial …
to generate images with high spatial and spectral resolution by combining high-spatial …