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.

Bibliographische Detailangaben
1. Verfasser:	Sikder, Debabrata
Weitere Verfasser:	Alam, Md. Golam Rabiul
Format:	Project report
Sprache:	English
Veröffentlicht:	Brac University 2024
Schlagworte:	Machine learning Deep learning Human activity recognition Recurrent neural networks Long short-term memory networks
Online Zugang:	http://hdl.handle.net/10361/23155

Ähnliche Einträge

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

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

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

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

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

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

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

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

Forecasting market movement in Dhaka Stock Exchange: LSTM vs. ARIMA
von: Chakraborty, Pranjal
Veröffentlicht: (2019)

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

Malware Detection Using Neural Network
von: Kayum, Syed Irfan, et al.
Veröffentlicht: (2021)

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

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

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

Empowering mobile network planning through deep learning: a path to democratization
von: Nabi, Syed Tauhidun
Veröffentlicht: (2024)

Prediction of human activity using machine learning
von: Tisha, Sadia Nasrin, et al.
Veröffentlicht: (2020)

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

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

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

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

Bang-lish sentiment classification using deep learning
von: Saleheen, Abrar, et al.
Veröffentlicht: (2023)

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

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

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

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

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

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

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

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

Human activity recognition and authentication system
von: ALam, Md. Zubaer
Veröffentlicht: (2024)

Visual object recognition using deep convolutional neural network
von: Ahmed, Sabbir
Veröffentlicht: (2017)

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

Predicting crime using deep learning
von: Shihab, Muhammad Nafees, et al.
Veröffentlicht: (2024)

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

Optical flow based violence detection from video footage using hybrid MobileNet and Bi-LSTM
von: Haque, Tashfia, et al.
Veröffentlicht: (2024)

Corn leaf disease detection using deep convolution neural network
von: Rabbi, Rawhatur, et al.
Veröffentlicht: (2023)

Traffic sign recognition using deep learning
von: Amir, Afia Binte, et al.
Veröffentlicht: (2020)

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

An efficient deep learning approach to detect skin Cancer
von: Islam, Ashfaqul, et al.
Veröffentlicht: (2022)

Learning a deep neural network for predicting phishing website
von: Das, Robat, et al.
Veröffentlicht: (2019)