In this letter, we address the interference mitigation problem caused by ground-based space surveillance radars on spaceborne debris monitoring radars. Suppression-based methods often involve high ...

The main objectives of a battery management system (BMS) are to monitor the state-of-charge (SoC) and state-of-health (SoH) of lithium-ion batteries (LIBs). Due to their coupled nature, the SoC and ...

Spectral super-resolution, which reconstructs hyperspectral images (HSI) from a single RGB image, has garnered increasing attention. Due to the limitations of CNN structures in spectral modeling and ...

However, the recently proposed Mamba deep learning model combined with State Space Models (SSMs) has enormous potential in long sequence modeling. Therefore, we have developed a novel place ...

On Monday, Maryland transportation leaders broke ground on a new, state-of-the-art air traffic control tower at Martin State Airport. The new facility will replace the airport's existing tower ...

To make up for the shortcomings of these two architectures, an emerging visual state space model (VMamba) is introduced. Motivated by this, this paper presents a NR-IQA method via VIsual State space ...

Image restoration is a critical task in low-level computer vision, aiming to restore high-quality images from degraded inputs. Various models, such as convolutional neural networks (CNNs), generative ...

Remote sensing images semantic segmentation is typically challenging due to the complexity of land cover information. Existing convolutional neural network (CNN)-based models lack the capability to ...

State space models (SSMs), particularly Mamba, have shown promise in NLP tasks and are increasingly applied to vision tasks. However, most Mamba-based vision models focus on network architecture and ...

Pansharpening aims to fuse the panchromatic (PAN) and low-resolution multispectral (LR-MS) images, finally generating the high-resolution multispectral (HR-MS) images by reconstructing the ...

In this paper, we propose a lightweight and efficient state-space model-based instance segmentation network named MambaInst, which extracts deep semantic features through a LightSSM Block consisting ...

Therefore, a high-performance time series prediction model is crucial for PHM. This paper focuses on the use of time series prediction models to achieve the prediction of key state parameters of the ...