Affect detection from arabic tweets using ensemble and deep learning techniques
نویسندگان
چکیده
منابع مشابه
Early detection of MS in fMRI images using deep learning techniques
Introduction & Objective:MS is a disease of the central nervous system in which the body makes a defensive attack on its tissues. The disease can affect the brain and spinal cord, causing a wide range of potential symptoms, including balance, movement and vision problems. MRI and fMRI images are a very important tool in the diagnosis and treatment of MS. The aim of this study was to provide...
متن کاملInfant Head Circumference Measurement Using Deep Learning Techniques
Infant's head circumference measurement and and its growth monitoring plays a crucial role in diagnosis the diseases which cause a deformation in the infant's head. Due to the fact that the contact measurement, which is performed using a tape measure and a caliper, has problems such as transmitting disease, infecting, not comfortable and disruption relaxing the baby, going to non-contact measur...
متن کاملLearning Negotiation Policies Using Ensemble-Based Drift Detection Techniques
In this work we compare drift detection techniques and we show how they can improve the performance of trade agents in multi-issue bilateral dynamic negotiations. In a dynamic negotiation the utility values and functions of trade agents can change on the fly. Intelligent trade agents must identify and take such drift in the competitors into account changing also the offer policies to improve th...
متن کاملAffect detection from non-stationary physiological data using ensemble classifiers
Affect detection from physiological signals has received considerable attention. One challenge is that physiological measures exhibit considerable variations over time, making classification of future data difficult. The present study addresses this issue by providing insights on how diagnostic physiological features of affect change over time. Affective physiological data (Electrocardiogram, E...
متن کاملImproving Sensor-Free Affect Detection Using Deep Learning
Affect detection has become a prominent area in student modeling in the last decade and considerable progress has been made in developing effective models. Many of the most successful models have leveraged physical and physiological sensors to accomplish this. While successful, such systems are difficult to deploy at scale due to economic and political constraints, limiting the utility of their...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of King Saud University - Computer and Information Sciences
سال: 2020
ISSN: 1319-1578
DOI: 10.1016/j.jksuci.2020.09.013