Results 41 to 50 of about 5,803,394 (295)
LAND USE CLASSIFICATION USING DEEP MULTITASK NETWORKS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Updated information on urban land use allows city planners and decision makers to conduct large scale monitoring of urban areas for sustainable urban growth.
J. R. Bergado, C. Persello, A. Stein
doaj +1 more source
Multitask Siamese Network for Remote Photoplethysmography and Respiration Estimation
Sensors, 2022 Heart and respiration rates represent important vital signs for the assessment of a person’s health condition. To estimate these vital signs accurately, we propose a multitask Siamese network model (MTS) that combines the advantages of the Siamese ...
Heejin Lee +6 more
doaj +1 more source
Multitask Learning for Fine-Grained Twitter Sentiment Analysis [PDF]
, 2017 Traditional sentiment analysis approaches tackle problems like ternary (3-category) and fine-grained (5-category) classification by learning the tasks separately.
Amini, Massih-Reza +2 more
core +2 more sources
Probabilistic Low-Rank Multitask Learning
IEEE Transactions on Neural Networks and Learning Systems, 2018 In this paper, we consider the problem of learning multiple related tasks simultaneously with the goal of improving the generalization performance of individual tasks. The key challenge is to effectively exploit the shared information across multiple tasks as well as preserve the discriminative information for each individual task.
Yu Kong, Ming Shao, Kang Li, Yun Fu
openaire +2 more sources
Multitask learning for blackmarket tweet detection [PDF]
Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2019 4 pages, IEEE/ACM International Conference on Social Networks Analysis and Mining (ASONAM ...
Arora, Udit +2 more
openaire +2 more sources
Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding
Future Internet, 2022 In recent years, deep learning-based sentiment analysis has received attention mainly because of the rise of social media and e-commerce. In this paper, we showcase the fact that the polarity detection and subjectivity detection subtasks of sentiment ...
Ranjan Satapathy +2 more
doaj +1 more source
IEEE Transactions on Geoscience and Remote Sensing, 2021 In this article, we present a deep multitask learning framework able to couple semantic segmentation and change detection using fully convolutional long short-term memory (LSTM) networks.
M. Papadomanolaki +2 more
semanticscholar +1 more source
Improve the Performance and Stability of Incremental Learning by a Similarity Harmonizing Mechanism
IEEE Access, 2022 Incremental learning involves processing continuous streams of information in real time without much incorporation of previous knowledge. It is crucial to humans and machine learning models.
Jing Ma, Mingjie Liao, Lei Zhang
doaj +1 more source
Self-Paced Multitask Learning with Shared Knowledge
, 2017 This paper introduces self-paced task selection to multitask learning, where instances from more closely related tasks are selected in a progression of easier-to-harder tasks, to emulate an effective human education strategy, but applied to multitask ...
Carbonell, Jaime, Murugesan, Keerthiram
core +1 more source
, 2018 Multitask learning has shown promising performance in many applications and many multitask models have been proposed. In order to identify an effective multitask model for a given multitask problem, we propose a learning framework called learning to multitask (L2MT).
Zhang, Yu, Wei, Ying, Yang, Qiang
openaire +2 more sources