Results 231 to 240 of about 12,744 (261)

Advances in Weakly Supervised Learning of Morphology

, 2015
openaire   +4 more sources

Some of the next articles are maybe not open access.

Related searches:

Towards Safe Weakly Supervised Learning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019
In this paper, we study weakly supervised learning where a large amount of data supervision is not accessible. This includes i) incomplete supervision, where only a small subset of labels is given, such as semi-supervised learning and domain adaptation; ii) inexact supervision, where only coarse-grained labels are given, such as multi-instance learning
Yu-Feng Li, Zhi-Hua Zhou, Yu-Feng Li
exaly   +3 more sources

Weakly Supervised Learning-based Table Detection

SN Computer Science, 2020
CNN has given the state-of-the-art results in computer vision and natural language processing (NLP) domain problems. This has motivated researchers to use deep learning-based techniques for document layout analysis. Due to recent advances in communication and in information technology, methods of data storage, extraction and processing are rapidly ...
A. A. Gurav, Manisha J. Nene
openaire   +1 more source

Learning from Mistakes: Weakly Supervised Learning of Rocks

2019 IEEE Canadian Conference of Electrical and Computer Engineering (CCECE), 2019
A standard method for teaching an object detector a new class is to fine-tune it with a fully-supervised image set. The issue with fully-supervised image sets are that they are tedious to create and rely on human annotators. In this work we demonstrate that a new class can be learned by leveraging the ‘mistakes’ of a pre-trained object detector under a
Justin Szoke-Sieswerda, Matthew Cross 0004, Leo Van Kampen, Kenneth A. McIsaac   +3 more
openaire   +1 more source

Weakly Supervised Deep Learning in Radiology

Radiology
This review explores the transition of deep learning in radiology from laborious fully supervised methods to more scalable weakly supervised methods, emphasizing the potential and challenges for future research.
Leo Misera, Gustav Müller-Franzes, Daniel Truhn, Jakob Nikolas Kather   +3 more
openaire   +2 more sources

Cyberbullying Detection with Weakly Supervised Machine Learning

Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, 2017
Detrimental online behavior such as harassment and cyberbullying is becoming a serious, large-scale problem damaging people’s lives. This phenomenon is creating a need for automated, data-driven techniques for analyzing and detecting such behaviors.
Elaheh Raisi, Bert Huang
openaire   +1 more source

Continuous affect recognition with weakly supervised learning

Multimedia Tools and Applications, 2019
Recognizing a person’s affective state from audio-visual signals is an essential capability for intelligent interaction. Insufficient training data and the unreliable labels of affective dimensions (e.g., valence and arousal) are two major challenges in continuous affect recognition. In this paper, we propose a weakly supervised learning approach based
Ercheng Pei, Dongmei Jiang, Mitchel Alioscha-Pérez, Hichem Sahli   +3 more
openaire   +1 more source

Discrepant multiple instance learning for weakly supervised object detection

Pattern Recognition, 2022
Songcen Xu, Jun Yue, Fang Wan
exaly  

Weakly Supervised Discriminative Learning With Spectral Constrained Generative Adversarial Network for Hyperspectral Anomaly Detection

IEEE Transactions on Neural Networks and Learning Systems, 2022
Weiying Xie, Qian Du, Yunsong Li
exaly  

Segmentation only uses sparse annotations: Unified weakly and semi-supervised learning in medical images

Medical Image Analysis, 2022
Feng Gao, Tao Song, Xiaochun Meng
exaly