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This letter presents Switch-SLAM, switching-based LiDAR-inertial-visual SLAM for degenerate environments, designed to tackle the challenges in degenerate environments for LiDAR and visual SLAM. Switch ...
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images. Some existing deep learning based methods are devoted to improving the model ...
Underwater imaging is often affected by light attenuation and scattering in water, leading to degraded visual quality, such as color distortion, reduced contrast, and noise. Existing underwater image ...
Hyperspectral image (HSI) classification is fundamental to numerous remote sensing applications, enabling detailed analysis of material properties and environmental conditions. Recent Mamba built upon ...
The rapid development of the large language model (LLM) presents huge opportunities for 6G communications – for example, network optimization and management – by allowing users to input task ...
In recent years, the rapid development of the unmanned aerial vehicle (UAV) technology has generated a large number of aerial photography images captured by UAV. Consequently, the object detection in ...
In hyperspectral images (HSIs), different land cover (LC) classes have distinct reflective characteristics at various wavelengths. Therefore, relying on only a few bands to distinguish all LC classes ...
Restoration tasks in low-level vision aim to restore high-quality (HQ) data from their low-quality (LQ) observations. To circumvents the difficulty of acquiring paired data in real scenarios, unpaired ...
The availability of unprecedented unsupervised training data, along with neural scaling laws, has resulted in an unprecedented surge in model size and compute requirements for serving/training large ...
Large language models (LLMs) have become increasingly popular due to their exceptional performance in various artificial intelligence applications. However, their development often suffers from the ...
Channel Deduction: A New Learning Framework to Acquire Channel From Outdated Samples and Coarse Estimate ...
Camouflaged objects often blend in with their surroundings, making the perception of a camouflaged object a more complex procedure. However, most neural-network-based methods that simulate the visual ...
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