An android application to predict human activity using a deep learning LSTM model

An android application to predict human activity using a deep learning LSTM model

This project report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2023.

Detalhes bibliográficos
Autor principal:	Sikder, Debabrata
Outros Autores:	Alam, Md. Golam Rabiul
Formato:	Project report
Idioma:	English
Publicado em:	Brac University 2024
Assuntos:	Machine learning Deep learning Human activity recognition Recurrent neural networks Long short-term memory networks
Acesso em linha:	http://hdl.handle.net/10361/23155

Registos relacionados

Predicting temperature of major cities using machine learning and deep learning
Por: Jaharabi, Wasiou, et al.
Publicado em: (2024)

Leveraging sequential deep learning models for detecting multitude of human action categories
Por: Pranta, Kazi Al Refat, et al.
Publicado em: (2024)

Deep learning based predictive analytics for decentralized content caching in hierarchical edge networks
Por: Chakraborty, Dhruba, et al.
Publicado em: (2022)

The influence of neuromarketing: machine learning based empirical analysis
Por: Muktadir, MD. Abdullah Al, et al.
Publicado em: (2024)

Sentiment analysis to determine employee job satisfaction using machine learning techniques
Por: Mouli, Nazifa, et al.
Publicado em: (2023)

Share market forecasting with LSTM neural network and sentimental trend prediction
Por: Rony, Ismail Hossain, et al.
Publicado em: (2020)

Time-Series Forecasting of Ethereum Price using Long Short-Term Memory (LSTM) Networks
Por: Al-Wasee, Mohammad Samin, et al.
Publicado em: (2022)

Conversion of Bengali speech to text using long short-term memory(LSTM)
Por: Chowdhury, Mohammad Fahim, et al.
Publicado em: (2021)

Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA
Por: Chakraborty, Pranjal
Publicado em: (2019)

Implementation of machine learning to estimate the air pollutants such as Carbon dioxide, methane, nitrous oxide and total greenhouse gas emissions in Bangladesh
Por: Biswas, Sunanda, et al.
Publicado em: (2022)

Malware Detection Using Neural Network
Por: Kayum, Syed Irfan, et al.
Publicado em: (2021)

Intracranial hemorrhage detection using CNN-LSTM fusion model
Por: Ahmed, Kazi sabab, et al.
Publicado em: (2022)

LSTM based content prediction for edge caching using federated learning approach
Por: Mazumder, Shafkat Ahmed, et al.
Publicado em: (2021)

Empowering mobile network planning through deep learning: a path to democratization
Por: Nabi, Syed Tauhidun
Publicado em: (2024)

Economic crisis prediction due to pandemic outbreak using machine learning
Por: Ahmed, Tanvir, et al.
Publicado em: (2021)

Prediction of human activity using machine learning
Por: Tisha, Sadia Nasrin, et al.
Publicado em: (2020)

Detection of violent activity in surveillance system using different deep learning techniques
Por: Chakravorty, Tirthendu Prosad, et al.
Publicado em: (2024)

A deep dive into node-level analysis with fusion RNN model for smart LTE network monitoring
Por: Islam, Md Rashidul
Publicado em: (2024)

A conventional & deep learning strategy for analyzing & detecting Bengali fake news in online medium
Por: Ahmed, Istiak, et al.
Publicado em: (2023)

Bang-lish sentiment classification using deep learning
Por: Saleheen, Abrar, et al.
Publicado em: (2023)

Silent voice: harnessing deep learning for lip-reading in Bangla
Por: Shaheen, Munia, et al.
Publicado em: (2024)

Human Activity Recognition using wearable body sensor by machine learning approach
Por: Promi, Sadia Tangim, et al.
Publicado em: (2020)

Economic crisis prediction due to pandemic outbreak using machine learning
Por: Ahmed, Tanvir, et al.
Publicado em: (2021)

Utilizing machine learning to project the nancial outcomes of reconnecting with potential customers of the same industry
Por: Hossain, Shoumik, et al.
Publicado em: (2022)

Rating detection by reviews using ML and NLP towards mobile phone recommendation
Por: Sarker, Md Wafi, et al.
Publicado em: (2023)

Bangali Handwritten characters classification using Deep Convolutional Neural Network
Por: Sikder, Shihab Uddin, et al.
Publicado em: (2022)

Damaged road detection using Image Processing and Deep Learning
Por: Swadesh, Shimran Mahbub, et al.
Publicado em: (2022)

Predicting regional accents of Bengali language using deep learning
Por: Ibrahim, Md. Abu, et al.
Publicado em: (2022)

Human activity recognition and authentication system
Por: ALam, Md. Zubaer
Publicado em: (2024)

Visual object recognition using deep convolutional neural network
Por: Ahmed, Sabbir
Publicado em: (2017)

Modelling and forecasting energy demand of Bangladesh using AI based algorithms
Por: Mahmud, Booshra Nazifa, et al.
Publicado em: (2019)

Predicting crime using deep learning
Por: Shihab, Muhammad Nafees, et al.
Publicado em: (2024)

A deep learning approach for prediction of ADHD using brain structure
Por: Siam, Shafin Ahad, et al.
Publicado em: (2024)

An efficient deep learning approach to classify white blood cells
Por: Turja, Afif Ibna Kadir Khan, et al.
Publicado em: (2024)

Cryptocurrency price prediction and forecasting using machine learning algorithm and long- short term memory mapping
Por: Zaman, Md. Sayeed Ibne, et al.
Publicado em: (2022)

Corn leaf disease detection using deep convolution neural network
Por: Rabbi, Rawhatur, et al.
Publicado em: (2023)

An efficient deep learning approach to detect skin Cancer
Por: Islam, Ashfaqul, et al.
Publicado em: (2022)

Learning a deep neural network for predicting phishing website
Por: Das, Robat, et al.
Publicado em: (2019)

Traffic sign recognition using deep learning
Por: Amir, Afia Binte, et al.
Publicado em: (2020)

Automated detection of Malignant Lesions in the ovary using deep learning models and XAI
Por: Ifty, Md. Hasin Sarwar, et al.
Publicado em: (2024)