4 papers
ScalePredictor: Instance-aware Scale Learning for Accurate Quantization of Vision Transformers
Changjun Li, Runqing Jiang, Lian Xu +3
Vision Transformers have achieved remarkable success in many fields, yet their deployment on edge devices remains challenging due to their substantial computational demands. Post-T…
UDHF2-Net: Uncertainty-diffusion-model-based High-Frequency TransFormer Network for Remotely Sensed Imagery Interpretation
Pengfei Zhang, Chang Li, Yongjun Zhang +3
Remotely sensed imagery interpretation (RSII) faces the three major problems: (1) objective representation of spatial distribution patterns; (2) edge uncertainty problem caused by…
Pack-PTQ: Advancing Post-training Quantization of Neural Networks by Pack-wise Reconstruction
Changjun Li, Runqing Jiang, Zhuo Song +3
Post-training quantization (PTQ) has evolved as a prominent solution for compressing complex models, which advocates a small calibration dataset and avoids end-to-end retraining. H…
ΩSFormer: Dual-Modal Ω-like Super-Resolution Transformer Network for Cross-scale and High-accuracy Terraced Field Vectorization Extraction
Chang Li, Yu Wang, Ce Zhang +1
Terraced field is a significant engineering practice for soil and water conservation (SWC). Terraced field extraction from remotely sensed imagery is the foundation for monitoring…