A brief introduction to weakly supervised learning
ZH Zhou - National science review, 2018 - academic.oup.com
Supervised learning techniques construct predictive models by learning from a large
number of training examples, where each training example has a label indicating its ground …
number of training examples, where each training example has a label indicating its ground …
Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Abstract Machine learning (ML) algorithms have made a tremendous impact in the field of
medical imaging. While medical imaging datasets have been growing in size, a challenge …
medical imaging. While medical imaging datasets have been growing in size, a challenge …
Attention-based deep multiple instance learning
Multiple instance learning (MIL) is a variation of supervised learning where a single class
label is assigned to a bag of instances. In this paper, we state the MIL problem as learning …
label is assigned to a bag of instances. In this paper, we state the MIL problem as learning …
Hopfield networks is all you need
H Ramsauer, B Schäfl, J Lehner, P Seidl… - ar**
We introduce a model for bidirectional retrieval of images and sentences through a deep,
multi-modal embedding of visual and natural language data. Unlike previous models that …
multi-modal embedding of visual and natural language data. Unlike previous models that …
A review on machine learning styles in computer vision—techniques and future directions
Computer applications have considerably shifted from single data processing to machine
learning in recent years due to the accessibility and availability of massive volumes of data …
learning in recent years due to the accessibility and availability of massive volumes of data …
Co-saliency detection via a self-paced multiple-instance learning framework
As an interesting and emerging topic, co-saliency detection aims at simultaneously
extracting common salient objects from a group of images. On one hand, traditional co …
extracting common salient objects from a group of images. On one hand, traditional co …