Results 11 to 20 of about 5,803,394 (295)

Multitask learning to predict successful weaning in critically ill ventilated patients: A retrospective analysis of the MIMIC-IV database [PDF]

Digital Health
Objective Weaning is an essential issue in critical care. This study explores the efficacy of multitask learning models in predicting successful weaning in critically ill ventilated patients using the Medical Information Mart for Intensive Care (MIMIC ...
Ming-Yen Lin, Hsin-You Chi, Wen-Cheng Chao   +2 more
doaj   +2 more sources

Trainable Weights for Multitask Learning

IEEE Access, 2023
The research on multi-task learning has been steadily increasing due to its advantages, such as preventing overfitting, averting catastrophic forgetting, solving multiple inseparable tasks, and coping with data shortage.
Chaeeun Ryu, Changwoo Lee, Hyuk Jin Choi, Chang-Hyun Lee, Byoungjun Jeon, Eui Kyu Chie, Young-Gon Kim   +6 more
doaj   +2 more sources

When Self-Supervised Learning Meets Scene Classification: Remote Sensing Scene Classification Based on a Multitask Learning Framework

Remote Sensing, 2020
In recent years, the development of convolutional neural networks (CNNs) has promoted continuous progress in scene classification of remote sensing images.
Zhicheng Zhao, Ze Luo, Jian Li, Can Chen, Yingchao Piao   +4 more
doaj   +3 more sources

Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective [PDF]

Computer Vision and Pattern Recognition, 2023
We aim at advancing blind image quality assessment (BIQA), which predicts the human perception of image quality without any reference information. We develop a general and automated multitask learning scheme for BIQA to exploit auxiliary knowledge from ...
Weixia Zhang, Guangtao Zhai, Ying Wei, Xiaokang Yang, Kede Ma   +4 more
semanticscholar   +1 more source

A Multiscale and Multitask Deep Learning Framework for Automatic Building Extraction

Remote Sensing, 2022
Detecting buildings, segmenting building footprints, and extracting building edges from high-resolution remote sensing images are vital in applications such as urban planning, change detection, smart cities, and map-making and updating.
Jichong Yin, Fang Wu, Yue Qiu, Anping Li, Chengyi Liu, Xianyong Gong   +5 more
doaj   +1 more source

Speech Emotion and Naturalness Recognitions With Multitask and Single-Task Learnings

IEEE Access, 2022
This paper evaluates speech emotion and naturalness recognitions by utilizing deep learning models with multitask learning and single-task learning approaches. The emotion model accommodates valence, arousal, and dominance attributes known as dimensional
Bagus Tris Atmaja, Akira Sasou, Masato Akagi   +2 more
doaj   +1 more source

BDD100K: A Diverse Driving Dataset for Heterogeneous Multitask Learning [PDF]

Computer Vision and Pattern Recognition, 2018
Datasets drive vision progress, yet existing driving datasets are impoverished in terms of visual content and supported tasks to study multitask learning for autonomous driving.
F. Yu, Haofeng Chen, Xin Wang, Wenqi Xian, Yingying Chen, Fangchen Liu, Vashisht Madhavan, Trevor Darrell   +7 more
semanticscholar   +1 more source

Stacker Scheduling and Repository Location Recommendation Based on Multi-Task Reinforcement Learning [PDF]

Jisuanji gongcheng, 2023
Stacker scheduling is an essential task in warehousing automation.Inbound-outbound efficiency and storage situations affect overall efficiency.When handling large-scale problems, traditional scheduling methods cannot achieve performance because ...
RAO Dongning, LUO Nanyue
doaj   +1 more source

Clustering by Errors: A Self-Organized Multitask Learning Method for Acoustic Scene Classification

Sensors, 2021
Acoustic scene classification (ASC) tries to inference information about the environment using audio segments. The inter-class similarity is a significant issue in ASC as acoustic scenes with different labels may sound quite similar.
Weiping Zheng, Zhenyao Mo, Gansen Zhao
doaj   +1 more source

Machine learning applied to the prediction of root architecture of soybean cultivars under two water availability conditions

Semina: Ciências Agrárias, 2022
The objective of this study was to evaluate the performance of four machine learning models, as well as multitask learning, to predict soybean root variables from simpler variables, under two water availability conditions.
Anunciene Barbosa Duarte, Dalton de Oliveira Ferreira, Lucas Borges Ferreria, Felipe Lopes da Silva   +3 more
doaj   +1 more source