Results 31 to 40 of about 13,981 (216)

A Probabilistic Fractional Order Physics Informed Mamba Kolmogorov‐Arnold Network for State‐of‐Charge Estimation in Grid‐Connected Battery Energy Storage Systems

Energy Science &Engineering, EarlyView.
This paper introduces the probabilistic fractional‐order Mam‐KAN (PFO‐Mam‐KAN) controller, a physics‐informed gray‐box framework for real‐time battery state‐of‐charge estimation. By unifying efficient Mamba encoders with uncertainty‐aware fractional physics, it achieves superior 0.31% RMSE accuracy and robust grid‐support operation under dynamic ...
Arun Kumar Rawat, Subhash Chandra, Vinay Kumar Deolia   +2 more
wiley   +1 more source

Mamba-SEUNet: Mamba UNet for Monaural Speech Enhancement

ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
In recent speech enhancement (SE) research, transformer and its variants have emerged as the predominant methodologies. However, the quadratic complexity of the self-attention mechanism imposes certain limitations on practical deployment. Mamba, as a novel state-space model (SSM), has gained widespread application in natural language processing and ...
Junyu Wang, Zizhen Lin, Tianrui Wang, Meng Ge, Longbiao Wang, Jianwu Dang 0001   +5 more
openaire   +2 more sources

Text-Guided Contrastive Mamba for Hyperspectral Image Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Hyperspectral image (HSI) classification is challenging due to their high spectral complexity and the need to model long-range dependencies. Although contrastive learning has shown promise, most existing approaches rely on convolutional neural networks ...
Baokai Zu, Zhengrui Yang, Yafang Li, Hongyuan Wang, Jianqiang Li, Ziping He   +5 more
doaj   +1 more source

R3Net: Recursive Residual Refinement Network Architecture for Decoder‐Free Medical Image Segmentation

Precision Radiation Oncology, EarlyView.
We propose R3Net, a decoder‐free medical image segmentation framework that recursively refines multiscale representations within the encoder using residual pathways. R3Net achieves competitive accuracy with reduced model complexity and improved computational efficiency across multiple medical imaging modalities.
Jing Huang, Yongkang Zhao, Yuhan Li, Zhitao Dai, Cheng Chen, Qiying Lai   +5 more
wiley   +1 more source

ET-Mamba: A Mamba Model for Encrypted Traffic Classification

Information
With the widespread use of encryption protocols on network data, fast and effective encryption traffic classification can improve the efficiency of traffic analysis. A resampling method combining Wasserstein GAN and random selection is proposed for solving the dataset imbalance problem, and it uses Wasserstein GAN for oversampling and random selection ...
Jian Xu, Liangbing Chen, Wenqian Xu, Longxuan Dai, Chenxi Wang, Lei Hu 0009   +5 more
openaire   +2 more sources

Los-mamba: A low-rank recursive mamba framework for mitigating stationary bias in trajectory prediction

Journal of King Saud University: Computer and Information Sciences
Trajectory prediction plays a key role in autonomous driving and intelligent transportation systems. Mamba performs well in modeling long sequences but struggles with short-term static or local motion features.
Yang Cui, Dong Guo, Lirui Liu, Yi Han
doaj   +1 more source

Spatial–Temporal–Spectral Mamba With Sparse Deformable Token Sequence for Enhanced MODIS Time-Series Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Although moderate resolution imaging spectroradiometer (MODIS) time-series data are critical for supporting dynamic, large-scale land cover land use classification, it is a challenging task to capture the subtle class signature information due to key ...
Zack Dewis, Zhengsen Xu, Yimin Zhu, Motasem Alkayid, Mabel Heffring, Lincoln Linlin Xu   +5 more
doaj   +1 more source

Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution [PDF]

IEEE transactions on multimedia
Recent progress in remote sensing image (RSI) super-resolution (SR) has exhibited remarkable performance using deep neural networks, e.g., Convolutional Neural Networks and Transformers.
Yi Xiao, Qiangqiang Yuan, Kui Jiang, Yuzeng Chen, Qiang Zhang, Chia-Wen Lin   +5 more
semanticscholar   +1 more source

A Lightweight Hybrid Network for Medical Image Segmentation With Adaptive Feature Selection

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurate medical image segmentation with low model complexity remains difficult because lesions are often small in scale and boundary cues are easily corrupted by noise. Although recent segmentation methods have achieved strong performance, many of them rely on increasingly complex architectures with high computational costs, limiting their ...
Zhouwei Lin, Yudong Xia, Pingping Wu, Han Lin, Qingsong Xu, Zheng Fan, Juan Tu, Jun Wu   +7 more
wiley   +1 more source

ms-mamba: Multi-scale mamba for time-series forecasting

Neurocomputing
The problem of Time-series Forecasting is generally addressed by recurrent, Transformer-based and the recently proposed Mamba-based architectures. However, existing architectures generally process their input at a single temporal scale, which may be sub-optimal for many tasks where information changes over multiple time scales.
Yusuf Meriç Karadağ, Talaz, Ismail, Kalkan, Sinan, Gursel Dino, Ipek   +3 more
openaire   +4 more sources