38 citations · 62 across the 4 of their papers we have counts for
4 papers
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
Sheng-Jun Huang, Yi Li, Yiming Sun +1
Active learning (AL) for multiple target models aims to reduce labeled data querying while effectively training multiple models concurrently. Existing AL algorithms often rely on i…
MUS-CDB: Mixed Uncertainty Sampling with Class Distribution Balancing for Active Annotation in Aerial Object Detection
Dong Liang, Jing-Wei Zhang, Ying-Peng Tang +1
Recent aerial object detection models rely on a large amount of labeled training data, which requires unaffordable manual labeling costs in large aerial scenes with dense objects.…
Video Frame Interpolation via Structure-Motion based Iterative Fusion
Xi Li, Meng Cao, Yingying Tang +4
Video Frame Interpolation synthesizes non-existent images between adjacent frames, with the aim of providing a smooth and consistent visual experience. Two approaches for solving t…
ALiPy: Active Learning in Python
Ying-Peng Tang, Guo-Xiang Li, Sheng-Jun Huang
Supervised machine learning methods usually require a large set of labeled examples for model training. However, in many real applications, there are plentiful unlabeled data but l…