Deep learning based arrhythmia classification on low-cost and low-compute MCU

Deep learning based arrhythmia classification on low-cost and low-compute MCU

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2023.

Xehetasun bibliografikoak
Egile Nagusiak:	Zishan, Md Abu Obaida, Shihab, H M, Rahman, Gazi Mashrur, Islam, Sabik Sadman, Riya, Maliha Alam
Beste egile batzuk:	Mukta, Jannatun Noor
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2023
Gaiak:	ECG Arrhythmia Low-cost Low-compute Low-power Machine learning Micro-controller Cognitive learning theory (Deep learning)
Sarrera elektronikoa:	http://hdl.handle.net/10361/22018

Antzeko izenburuak

Analysis of deep learning models on low-light pest detection
nork: Irtiza, Md. Samin, et al.
Argitaratua: (2023)

Predicting Macroeconomic and Macrofinancial Stress in Low-Income Countries /
nork: Weisfeld, Hans
Argitaratua: (2020)

Low-income housing : multi-dimensional research perspectives /
Argitaratua: (2001)

Machine learning approach for ECG analysis and predicting different heart diseases
nork: Tithi, Sushmita Roy, et al.
Argitaratua: (2019)

Understanding the potential of Maggi soups among low income people in Dhaka city
nork: Shemanto, Ashfaqur Rahman
Argitaratua: (2017)

Skin cancer detection and classification using multiple optimized deep convolutional neural network
nork: Sakir, Adnan, et al.
Argitaratua: (2023)

Classification of Bangla regional languages and recognition of artificial Bangla speech using deep learning
nork: Hossain, Prommy Sultana
Argitaratua: (2022)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
nork: Hasan, M. M. Kamrul, et al.
Argitaratua: (2022)

Heart disease prediction using machine learning algorithms
nork: Ali, Musfiq, et al.
Argitaratua: (2019)

Classification and Explanation of Different Internet of Things (IoT) Network Attacks using Machine Learning, Deep Learning and XAI
nork: Tasnim, Anika, et al.
Argitaratua: (2022)

An implementation and analysis of deep learning models for the detection of wheat diseases
nork: Zubair, Ahmad, et al.
Argitaratua: (2024)

Exploring consumer attitude for Maggi seasoning among the low income segment in Dhaka
nork: Imam, Tausif
Argitaratua: (2016)

Analysis of the impact of online education using EEG signals and machine learning algorithms
nork: Hoque, Ehsanul, et al.
Argitaratua: (2021)

Growth and development pattern of low birth weight infants in rural Bangladesh
nork: Gazi, Rukhsana, et al.
Argitaratua: (2019)

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
nork: Fahim, Kaji Mehedi Hasan, et al.
Argitaratua: (2024)

Yoga posture recognition using the deep learning process
nork: Islam, Abidul, et al.
Argitaratua: (2023)

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

Mapping disparities in education across low- and middle-income countries
nork: Local Burden of Disease Educational Attainment Collaborators
Argitaratua: (2022)

Crop prediction based on geographical and climatic data using machine learning and deep learning
nork: Alif, Al Amin, et al.
Argitaratua: (2019)

Using deep learning algorithms to detect violent activities
nork: Ammar, S.M. Rojin, et al.
Argitaratua: (2019)

Public vehicle ETA system using machine learning
nork: Kabir, Md. Miraz, et al.
Argitaratua: (2018)

Predicting depression in Bangladeshi undergraduates using machine learning
nork: Choudhury, Ahnaf Atef, et al.
Argitaratua: (2019)

Affordable housing for low-income group, Purbachal, Dhaka
nork: Binu, Nishat Yasmin
Argitaratua: (2024)

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
nork: Toufique, S.M, et al.
Argitaratua: (2024)

Hypothesizing precise cancer treatments based on patient survival using machine learning & deep learning
nork: Sakib, Hasibul, et al.
Argitaratua: (2024)

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
nork: Rayhan, Mohammad, et al.
Argitaratua: (2020)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
nork: Rafat, Md. Tasbi, et al.
Argitaratua: (2023)

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

Prostate cancer detection using deep learning neural network with transfer learning approach
nork: Badhon, Ariful Islam Mahmud, et al.
Argitaratua: (2022)

Deep learning /
nork: Goodfellow, Ian
Argitaratua: (2016)

Alumni opportunities using machine learning
nork: Siaum, Arshif Sharlimin, et al.
Argitaratua: (2019)

Machine learning as an indicator for breast cancer prediction
nork: Shadman, Tahsin Mohammed, et al.
Argitaratua: (2019)

Chronic kidney disease detection using ensemble classi ers and feature set reduction
nork: Shawan, Naveed Rahman, et al.
Argitaratua: (2019)

Lifting the lockdown: What are the options for low and middle-income countries?
nork: Chowdhury, Rajiv, et al.
Argitaratua: (2022)

Classification of retinal diseases from OCT images using deep learning models
nork: Mokarrom, Md Saif, et al.
Argitaratua: (2024)

Deep learning-based waste classification system for efficient waste management
nork: Nakib, Abdullah Al, et al.
Argitaratua: (2022)

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

Mapping local patterns of childhood overweight and wasting in low- and middle-income countries between 2000 and 2017
nork: LBD Double Burden of Malnutrition Collaborators
Argitaratua: (2022)

A Study of gainful employment of learners receiving skills training in the informal sector using Machine Learning
nork: Raizan, Syed Ahsan, et al.
Argitaratua: (2021)

Low birth weight(LBW) was the major predictor of infant deaths: evidence from a prospective study in rural Bangladesh
nork: Gazi, Rukhsana, et al.
Argitaratua: (2020)