Emotion Detection Using Convolution Neural Network, Expert System and Deep Learning Approach
نویسندگان
چکیده
منابع مشابه
A Deep Learning Approach for Network Intrusion Detection System
A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organization. However, many challenges arise while developing a flexible and effective NIDS for unforeseen and unpredictable attacks. In this work, we propose a deep learning based approach to implement such an effective and flexible NIDS. We use Self-taught Learning (STL), a dee...
متن کاملText Emotion Detection using Neural Network
Text emotion detection refers to identifying the type of emotion getting used by the text. The process involves two process training and testing. The training section involves training the classifier with the text and the testing section involves the identification of the type of text used. After this accuracy of the classifier is checked by measuring how many correct labels of the text does th...
متن کاملCompressed Learning: A Deep Neural Network Approach
This work presents a novel deep learning approach to Compressed-Learning. Jointly optimizing the sensing and inference operators. Outperforming state-of-the-art CL methods on MNIST and CIFAR10. Extendible to numerous CL applications. The research leading to these results has received funding from the European Research Council under European Union's Seventh Framework Program, ERC Grant agre...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Tweet Sarcasm Detection Using Deep Neural Network
Sarcasm detection has been modeled as a binary document classification task, with rich features being defined manually over input documents. Traditional models employ discrete manual features to address the task, with much research effect being devoted to the design of effective feature templates. We investigate the use of neural network for tweet sarcasm detection, and compare the effects of t...
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: Bioscience Biotechnology Research Communications
سال: 2020
ISSN: 0974-6455,2321-4007
DOI: 10.21786/bbrc/13.13/34