Latest Research
CloudS2Mask: A novel deep learning approach for improved cloud and cloud shadow masking in Sentinel-2 imagery
DPIRD-DMA/CloudS2Mask
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Remote Sensing of Environment 2024
Precise and efficient cloud and cloud shadow masking methods are required for the automated use of this data.
Cross-Domain Feature Augmentation for Domain Generalization
Existing methods focus on learning invariance across domains to enhance model robustness, and data augmentation has been widely used to learn invariant predictors, with most methods performing augmentation in the input space.
Achieving Fairness Through Channel Pruning for Dermatological Disease Diagnosis
Numerous studies have revealed that deep learning-based medical image classification models may exhibit bias towards specific demographic attributes, such as race, gender, and age.
StraightPCF: Straight Point Cloud Filtering
Point cloud filtering is a fundamental 3D vision task, which aims to remove noise while recovering the underlying clean surfaces.
TEDNet: Twin Encoder Decoder Neural Network for 2D Camera and LiDAR Road Detection
Robust road surface estimation is required for autonomous ground vehicles to navigate safely.
Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
For fine-grained language understanding, we train a Multimodal Large Language Model to refine the captions of the images.
EfficientTrain++: Generalized Curriculum Learning for Efficient Visual Backbone Training
These patterns, when observed through frequency and spatial domains, incorporate lower-frequency components, and the natural image contents without distortion or data augmentation.
RDPN6D: Residual-based Dense Point-wise Network for 6Dof Object Pose Estimation Based on RGB-D Images
In this work, we introduce a novel method for calculating the 6DoF pose of an object using a single RGB-D image.
Evaluating LLMs at Evaluating Temporal Generalization
The rapid advancement of Large Language Models (LLMs) highlights the urgent need for evolving evaluation methodologies that keep pace with improvements in language comprehension and information processing.
Self-Distillation Improves DNA Sequence Inference
Self-supervised pretraining (SSP) has been recognized as a method to enhance prediction accuracy in various downstream tasks.
