Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2020.

Détails bibliographiques
Auteurs principaux:	Arafat, Sheikh Mohammad, Islam, Rifatul, Rafi, Ishraque Arefin, Islam, Md. Rashedul
Autres auteurs:	Alam, Md. Golam Rabiul
Format:	Thèse
Langue:	en_US
Publié:	Brac University 2021
Sujets:	Effectiveness of Marketing Emotional States Deep Learning Supervised Machine Learning LSTM-RNN MFCC
Accès en ligne:	http://hdl.handle.net/10361/14468

Documents similaires

Predicting crime using deep learning
par: Shihab, Muhammad Nafees, et autres
Publié: (2024)

Bangla speech recognition using 1D CNN and LSTM with different dimension reduction techniques
par: Nirjhor, S M Mahsanul Islam, et autres
Publié: (2019)

RED-LSTM: Real time emotion detection using LSTM
par: Labiba, Mansura Rahman, et autres
Publié: (2023)

Speech emotion detection using supervised, unsupervised and feature selection algorithms
par: Rifat, Abu Nuraiya Mahfuza Yesmin, et autres
Publié: (2019)

Human sentiment analysis using natural language processing
par: Shamya, Md. Shamiul Haque Khan, et autres
Publié: (2024)

Analyzing area-wise air pollution level using machine learning for a better future
par: Sihan, Sk. Atik Tajwar, et autres
Publié: (2021)

Performance analysis of deep learning algorithms for Intrusion Detection System(IDS) of IoT Security
par: Fiha, Yeamin Jahan, et autres
Publié: (2022)

Stock Market Price movement prediction using RNN and Point-weight Sentiment
par: Uddin, S. M. Rageeb Noor, et autres
Publié: (2022)

Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
par: Chakraborty, Dhruba, et autres
Publié: (2022)

A texture based industrial fault diagnosis model using Gammatone Filter Bank and transfer learning
par: Morshed, Atique, et autres
Publié: (2021)

Learning a deep neural network for predicting phishing website
par: Das, Robat, et autres
Publié: (2019)

Dhaka Stock Exchange stock price prediction using Machine Learning and Deep Learning Models
par: Barua, Debalina
Publié: (2023)

Multimodal emotion recognition from Speech and text using heterogeneous ensemble techniques
par: Rafidul Islam, Sheikh Md, et autres
Publié: (2022)

Early threat warning via speech and emotion recognition from voice calls
par: Ishtiak, Ifaz, et autres
Publié: (2019)

Recognition of Bangladeshi sign language from 2D videos using openpose and LSTM based RNN
par: Dewanjee, Tanmoy, et autres
Publié: (2021)

Predicting regional accents of Bengali language using deep learning
par: Ibrahim, Md. Abu, et autres
Publié: (2022)

A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
par: Ahmed, Istiak, et autres
Publié: (2023)

Analysis of financial data on the time series using data from the stock market
par: Shachcha, Ifad Bhuiyan, et autres
Publié: (2022)

Mental health analysis of cancer-diagnosed patients with the lowest survival rate and their caregivers
par: Orchi, Irin Hoque, et autres
Publié: (2023)

Hybrid recommendation system of intelligent captioning using deep learning networks
par: Wasi, Ahamed Al, et autres
Publié: (2024)

Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
par: Ahasan, Md. Mubtasim, et autres
Publié: (2022)

Electroencephalogram based Emotion Recognition with Graph Convolutional Network Model
par: Islam, Md. Tahmidul, et autres
Publié: (2023)

Emotional intelligence : why it can matter more than IQ /
par: Goleman, Daniel
Publié: (1996)

Behavior change analysis due to violent video gaming using deep learning models
par: Rahman, Akhlak Ur, et autres
Publié: (2024)

Emotional intelligence /
par: Goleman, Daniel
Publié: (1995)

Emotion in interaction
par: Peräkylä, Anssi

Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
par: Zaman, Md. Sayeed Ibne, et autres
Publié: (2022)

Emotion detection for Bangla language
par: Rushan, Rowshan Rahman, et autres
Publié: (2024)

Recognizing sentimental emotions in text by using Machine Learning
par: Bushra, Tabassum Khan, et autres
Publié: (2023)

TinyML for emotion detection in voice signals: evaluating and proposing algorithms for IoT wearable devices
par: Ahmed, Hasibul Hasan, et autres
Publié: (2024)

Breast cancer prediction using different machine learning models
par: Khandker Al- Muhaimin, et autres
Publié: (2020)

Parent’s perception and practices on socio-emotional development of 0-3 years old children
par: Begum, Iffat Ara
Publié: (2023)

Emotional discipline : the power to choose how you feel : 5 life changing steps to feeling better every day /
par: Manz, Charles C.
Publié: (2003)

Study on human emotion based on facial expressions through human machine communication
par: Murshed, Tahmin Aysha, et autres
Publié: (2021)

Exploring cognitive load and emotional states for the visually impaired
par: Afroz, Sharmin, et autres
Publié: (2019)

Automated image caption generator in Bangla using multimodal learning
par: Rodoshi, Mashiat Hasin, et autres
Publié: (2023)

Demand forecasting on supply chain using ML and NN
par: Hridi, Naoshin Anzum, et autres
Publié: (2023)

A deep learning approach to integrate human-level understanding in a Chatbot
par: Al Mamun, Amirul Islam, et autres
Publié: (2021)

Exploring the perceptions of parents on playful parenting and preschool children’s socio-emotional well-being
par: Zahan, Sharmin
Publié: (2024)

Deep learning approaches to EEG and fMRI data: a comparative study for sleep stage classification
par: Tanvir, Farhan, et autres
Publié: (2024)