Results 51 to 60 of about 6,939 (213)

An electroencephalography sleep staging model based on bidirectional Mamba combining synergistic attention with interactive convolution

Sleep Research, Volume 3, Issue 2, Page 135-149, June 2026.
Abstract Background This study presents SIMSleepSM, a novel single‐channel electroencephalography (EEG) sleep staging model. It addresses two primary challenges: insufficient modeling of long‐range temporal dependencies combined with limited multi‐scale feature extraction, and poor accuracy in identifying the N1 stage.
Ya‐mei Xu, Ding‐Yuan An
wiley   +1 more source

Hi-Mamba: Hierarchical Mamba for Efficient Image Super-Resolution

CoRR
State Space Models (SSM), such as Mamba, have shown strong representation ability in modeling long-range dependency with linear complexity, achieving successful applications from high-level to low-level vision tasks. However, SSM's sequential nature necessitates multiple scans in different directions to compensate for the loss of spatial dependency ...
Junbo Qiao, Jincheng Liao, Wei Li 0002, Yulun Zhang 0001, Yong Guo, Yi Wen, Zhangxizi Qiu, Jiao Xie, Jie Hu 0021, Shaohui Lin   +9 more
openaire   +4 more sources

Rose-Mamba-YOLO: an enhanced framework for efficient and accurate greenhouse rose monitoring

Frontiers in Plant Science
Accurately detecting roses in UAV-captured greenhouse imagery presents significant challenges due to occlusions, scale variability, and complex environmental conditions.
Sicheng You, Boheng Li, Yijia Chen, Zhiyan Ren, Yongying Liu, Qingyang Wu, Jianghan Tao, Zhijie Zhang, Chenyu Zhang, Feng Xue, Yulun Chen, Guochen Zhang, Jundong Chen, Jiaqi Wang, Fan Zhao   +14 more
doaj   +1 more source

YOLOv5-MDS: Target Detection Model for PCB Defect Inspection Based on YOLOv5 Integrated With Mamba Architecture

IEEE Access
The Printed Circuit Board (PCB), which serves as the foundational component of numerous electronic devices, exhibits a complex relationship between its quality and the lifespan and performance of those products.
Deming Guo, Qi Xi, Long Zhang, Jing Wang, Yilong Ye, Ziyi Zeng   +5 more
doaj   +1 more source

Rapid and High‐Accuracy Three‐Dimensional Airborne Transient Electromagnetic Forward Modeling Based on Machine Learning

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.
Abstract Conventional numerical methods for computing three‐dimensional (3D) airborne transient electromagnetic (ATEM) forward modeling suffer from low computational efficiency and high computational cost. Although deep learning techniques have achieved some progress in accelerating low‐dimensional ATEM forward modeling, high‐accuracy and efficient 3D ...
Xuben Wang, Shuang Wang, Peifan Jiang, Fei Deng, Yuanhao Li   +4 more
wiley   +1 more source

MCST-Mamba: Multivariate Mamba-Based Model for Traffic Prediction

GLOBECOM 2025 - 2025 IEEE Global Communications Conference
Submitted to the Communications Software and Multimedia track of the 2025 IEEE Global Communications ...
Mohamed Hamad, Mohamed Mabrok, Nizar Zorba   +2 more
openaire   +2 more sources

A Deep Learning-Based Solution to the Class Imbalance Problem in High-Resolution Land Cover Classification

Remote Sensing
Class imbalance (CI) poses a significant challenge in machine learning, characterized by a substantial disparity in sample sizes between majority and minority classes, leading to a pronounced “long-tail effect” in statistical distributions and subsequent
Pengdi Chen, Yong Liu, Yuanrui Ren, Baoan Zhang, Yuan Zhao   +4 more
doaj   +1 more source

ST‐TFFM‐Observer: A Global Ionospheric TEC Prediction Model Based on Dynamic System Theory With Enhanced Time‐Frequency Dependence Modeling

Space Weather, Volume 24, Issue 6, June 2026.
Abstract ST‐Observer is a novel proposed spatiotemporal prediction model based on dynamic system theory, which has been proven to be superior to existing models in multiple spatiotemporal prediction tasks. However, its structural design results in weak time dependent modeling capabilities and a lack of frequency dependent modeling capabilities.
Liwei Sun, Haijun Liu, Huijun Le, Jing Yuan, Shijia Li, Xingyue Yao, Guoming Yuan   +6 more
wiley   +1 more source

YOLO-BSMamba: A YOLOv8s-Based Model for Tomato Leaf Disease Detection in Complex Backgrounds

Agronomy
The precise identification of diseases in tomato leaves is of great importance for precise target pesticide application in a complex background scenario. Existing models often have difficulty capturing long-range dependencies and fine-grained features in
Zongfang Liu, Xiangyun Guo, Tian Zhao, Shuang Liang   +3 more
doaj   +1 more source

Exploring State Space Models in LiDAR Point Cloud Segmentation [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Mamba has achieved significant success in various fields due to its ability to efficiently model long-range dependencies with linear complexity. However, its application in LiDAR point cloud processing is still in its early stages, facing challenges such
D. Lu, L. Xu, R. Wang, J. Li
doaj   +1 more source