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 …
Predicting lymph node metastasis using histopathological images based on multiple instance learning with deep graph convolution
Multiple instance learning (MIL) is a typical weakly-supervised learning method where the
label is associated with a bag of instances instead of a single instance. Despite extensive …
label is associated with a bag of instances instead of a single instance. Despite extensive …
A benchmark and comparison of active learning for logistic regression
Logistic regression is by far the most widely used classifier in real-world applications. In this
paper, we benchmark the state-of-the-art active learning methods for logistic regression and …
paper, we benchmark the state-of-the-art active learning methods for logistic regression and …
Real-time incident prediction for online service systems
Incidents in online service systems could dramatically degrade system availability and
destroy user experience. To guarantee service quality and reduce economic loss, it is …
destroy user experience. To guarantee service quality and reduce economic loss, it is …
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 …
Multiple instance differentiation learning for active object detection
Despite the substantial progress of active learning for image recognition, there lacks a
systematic investigation of instance-level active learning for object detection. In this paper …
systematic investigation of instance-level active learning for object detection. In this paper …
Active learning for biomedical text classification based on automatically generated regular expressions
Biomedical text classification algorithms, which currently support clinical decision-making
processes, call for expensive training texts due to the low availability of labeled corpus and …
processes, call for expensive training texts due to the low availability of labeled corpus and …
Active semi-supervised learning for biological data classification
G Camargo, PH Bugatti, PTM Saito - PLoS One, 2020 - journals.plos.org
Due to datasets have continuously grown, efforts have been performed in the attempt to
solve the problem related to the large amount of unlabeled data in disproportion to the …
solve the problem related to the large amount of unlabeled data in disproportion to the …
Named Entity Recognition using CRF with Active Learning Algorithm in English Texts
B VeeraSekharReddy, KS Rao… - 2022 6th International …, 2022 - ieeexplore.ieee.org
Various Natural Language Processing (NLP) applications rely on Named Entity Recognition
(NER) to help them sift through mountains of unstructured text data and find the information …
(NER) to help them sift through mountains of unstructured text data and find the information …
Multiple instance learning for multiple diverse hyperspectral target characterizations
A practical hyperspectral target characterization task estimates a target signature from
imprecisely labeled training data. The imprecisions arise from the characteristics of the real …
imprecisely labeled training data. The imprecisions arise from the characteristics of the real …