Scientists Discover the Brain Can Rewire Itself To Truly Multitask

Extensive practice can rewire the brain so a learned skill runs more automatically, making some forms of true multitasking ...
IEEE

Multitask Learning for Object Localization With Deep Reinforcement Learning

Abstract: In object localization, methods based on a top-down search strategy that focus on learning a policy have been widely researched. The performance of these methods relies heavily on the policy ...
Frontiers

Deep learning for multitask prediction on thyroid nodule frozen sections

Preoperative ambiguous thyroid nodules often depend on intraoperative frozen sections for surgical planning, but misdiagnosis can occur due to low-quality frozen sections, limited diagnostic time, and ...
GitHub

Transfer and Multi-task Reinforcement Learning

Reinforcement Learning (RL) is a learning paradigm to solve many decision-making problems, which are usually formalized as Markov Decision Processes (MDP). Recently, Deep Reinforcement Learning (DRL) ...
C&EN

Deep Multitask Learning-Driven Discovery of New Compounds Targeting Leishmania infantum

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Classification: (i) if duplicates presented discordance in ...
Scientific Research Publishing

Crawshaw, M. (2020) Multi-Task Learning with Deep Neural Networks: A Survey.

ABSTRACT: Thoracic diseases pose significant risks to an individual's chest health and are among the most perilous medical diseases. They can impact either one or both lungs, which leads to a severe ...
Frontiers

Automatic tongue image quality assessment using a multi-task deep learning model

The quality of tongue images has a significant influence on the performance of tongue diagnosis in Chinese medicine. During the acquisition process, the quality of the tongue image is easily affected ...
IEEE

Framework for Deep Learning-Based Language Models Using Multi-Task Learning in Natural Language Understanding: A Systematic Literature Review and Future Directions

Abstract: Learning human languages is a difficult task for a computer. However, Deep Learning (DL) techniques have enhanced performance significantly for almost all-natural language processing (NLP) ...