Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
A survey on curriculum learning
Curriculum learning (CL) is a training strategy that trains a machine learning model from
easier data to harder data, which imitates the meaningful learning order in human curricula …
easier data to harder data, which imitates the meaningful learning order in human curricula …
A survey on deep active learning: Recent advances and new frontiers
Active learning seeks to achieve strong performance with fewer training samples. It does this
by iteratively asking an oracle to label newly selected samples in a human-in-the-loop …
by iteratively asking an oracle to label newly selected samples in a human-in-the-loop …
Curriculum learning: A survey
Training machine learning models in a meaningful order, from the easy samples to the hard
ones, using curriculum learning can provide performance improvements over the standard …
ones, using curriculum learning can provide performance improvements over the standard …
Multiple instance active learning for object detection
Despite the substantial progress of active learning for image recognition, there still lacks an
instance-level active learning method specified for object detection. In this paper, we …
instance-level active learning method specified for object detection. In this paper, we …
[PDF][PDF] A Comparative Survey: Benchmarking for Pool-based Active Learning.
Active learning (AL) is a subfield of machine learning (ML) in which a learning algorithm
aims to achieve good accuracy with fewer training samples by interactively querying the …
aims to achieve good accuracy with fewer training samples by interactively querying the …
Active learning and bayesian optimization: A unified perspective to learn with a goal
Science and Engineering applications are typically associated with expensive optimization
problem to identify optimal design solutions and states of the system of interest. Bayesian …
problem to identify optimal design solutions and states of the system of interest. Bayesian …
Similarity-based active learning methods
Active Learning has been a popular method to circumvent the labeling cost in machine
learning methods. The majority of active learning approaches can be classified into two …
learning methods. The majority of active learning approaches can be classified into two …
Contrastive coding for active learning under class distribution mismatch
Active learning (AL) is successful based on the assumption that labeled and unlabeled data
are obtained from the same class distribution. However, its performance deteriorates under …
are obtained from the same class distribution. However, its performance deteriorates under …
Symmetric self-paced learning for domain generalization
Deep learning methods often suffer performance degradation due to domain shift, where
discrepancies exist between training and testing data distributions. Domain generalization …
discrepancies exist between training and testing data distributions. Domain generalization …
Exploring diversity-based active learning for 3d object detection in autonomous driving
3D object detection has recently received much attention due to its great potential in
autonomous vehicle (AV). The success of deep learning based object detectors relies on the …
autonomous vehicle (AV). The success of deep learning based object detectors relies on the …