most citedA Novel Scene Coupling Semantic Mask Network for Remote Sensing Image Segmentation

2 citations · 6 across the 10 of their papers we have counts for

collaborators

15 papers

cs.LG2025

Ada-MoGE: Adaptive Mixture of Gaussian Expert Model for Time Series Forecasting

Zhenliang Ni, Xiaowen Ma, Zhenkai Wu +3

Multivariate time series forecasts are widely used, such as industrial, transportation and financial forecasts. However, the dominant frequencies in time series may shift with the…

cs.LG2025

Expert Merging: Model Merging with Unsupervised Expert Alignment and Importance-Guided Layer Chunking

Dengming Zhang, Xiaowen Ma, Zhenliang Ni +4

Model merging, which combines multiple domain-specialized experts into a single model, offers a practical path to endow Large Language Models (LLMs) and Multimodal Large Language M…

cs.CV2025

Spatial-Spectral Binarized Neural Network for Panchromatic and Multi-spectral Images Fusion

Yizhen Jiang, Mengting Ma, Anqi Zhu +3

Remote sensing pansharpening aims to reconstruct spatial-spectral properties during the fusion of panchromatic (PAN) images and low-resolution multi-spectral (LR-MS) images, finall…

cs.LG2025

TimeExpert: Boosting Long Time Series Forecasting with Temporal Mix of Experts

Xiaowen Ma, Shuning Ge, Fan Yang +5

Transformer-based architectures dominate time series modeling by enabling global attention over all timestamps, yet their rigid 'one-size-fits-all' context aggregation fails to add…

cs.CV2025

Cott-ADNet: Lightweight Real-Time Cotton Boll and Flower Detection Under Field Conditions

Rui-Feng Wang, Mingrui Xu, Matthew C Bauer +3

Cotton is one of the most important natural fiber crops worldwide, yet harvesting remains limited by labor-intensive manual picking, low efficiency, and yield losses from missing t…

cs.CV20251 cited

Contrastive Prompt Clustering for Weakly Supervised Semantic Segmentation

Wangyu Wu, Zhenhong Chen, Xiaowen Ma +6

Weakly Supervised Semantic Segmentation (WSSS) with image-level labels has gained attention for its cost-effectiveness. Most existing methods emphasize inter-class separation, ofte…