Empowering mobile network planning through deep learning: a path to democratization

Empowering mobile network planning through deep learning: a path to democratization

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

Bibliografiske detaljer
Hovedforfatter:	Nabi, Syed Tauhidun
Andre forfattere:	Alam, Golam Rabiul
Format:	Thesis
Sprog:	English
Udgivet:	Brac University 2024
Fag:	LTE networks Network planning Machine learning Deep learning Resource management Long-Term Evolution (Telecommunications)
Online adgang:	http://hdl.handle.net/10361/23113

Lignende værker

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

An android application to predict human activity using a deep learning LSTM model
af: Sikder, Debabrata
Udgivet: (2024)

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

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

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

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

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

A modern technique to detect potholes by Computer Vision and Deep Learning
af: Saif, Muntasir Mahmud, et al.
Udgivet: (2023)

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

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

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

Application of CNN based architectures in detection of distracted drivers
af: Arafin, Irfana, et al.
Udgivet: (2023)

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

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

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

Cooperative game theory based load balancing in long term evolution network
af: Intesar, Sadia, et al.
Udgivet: (2016)

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

Smart companion agent for mental well-being through Deep Learning and NLP
af: Khan, Rafiur, et al.
Udgivet: (2021)

Real-time mastitis detection in livestock using deep learning and machine learning leveraging edge devices
af: Ghosh, Kawshik Kumar, et al.
Udgivet: (2023)

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

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

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

Comparative analysis and implementation of credit risk prediction through distinct machine learning models
af: Turjo, Aquib Abtahi, et al.
Udgivet: (2021)

DeepWPD: A deep learning based wavelet packet decomposition to remove Moiré pattern from screen capture images.
af: Khan, Ibrahim
Udgivet: (2023)

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

Document template identification and data extraction using machine learning and deep learning approach
af: Roy, Kaushik, et al.
Udgivet: (2024)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
af: Islam, Zahedul, et al.
Udgivet: (2023)

Predicting effectiveness of marketing through analyzing emotional context in advertisement using deep learning
af: Arafat, Sheikh Mohammad, et al.
Udgivet: (2021)

Real-time foul detection in football matches using machine learning techniques
af: Siddiqui, Bishal Sadi, et al.
Udgivet: (2024)

Behavior change analysis due to violent video gaming using deep learning models
af: Rahman, Akhlak Ur, et al.
Udgivet: (2024)

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

Verifying online signatures through an iterative device independent model
af: Tahsin, Samiha, et al.
Udgivet: (2024)

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

Deep learning based arrhythmia classification on low-cost and low-compute MCU
af: Zishan, Md Abu Obaida, et al.
Udgivet: (2023)

An interpretable transformer based approach to classify Malaria from blood cell images
af: Islam, Mehafuza, et al.
Udgivet: (2023)

A deep learning approach towards soft biometrics attributes prediction using CNN
af: Kibria, Maharab, et al.
Udgivet: (2022)

Deep learning-based real-time pothole detection for avoiding road accident
af: Basher, Rafsan, et al.
Udgivet: (2022)

Detecting self-esteem level and depressive indication due to different parenting style using supervised learning techniques
af: Al Taawab, Abdullah, et al.
Udgivet: (2022)

Demystifying second hand car market in Bangladesh using multimodal machine learning techniques
af: Islam, Roman, et al.
Udgivet: (2024)

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