Analysis of uncertainty in different neural network structures using Monte Carlo Dropout

Analysis of uncertainty in different neural network structures using Monte Carlo Dropout

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

Xehetasun bibliografikoak
Egile Nagusiak:	Islam, Md. Farhadul, Zabeen, Sarah, Rahman, Fardin Bin, Islam, Md. Azharul, Kibria, Fahmid Bin
Beste egile batzuk:	Rasel, Annajiat Alim
Formatua:	Thesis
Hizkuntza:	English
Argitaratua:	Brac University 2024
Gaiak:	Deep learning Neural network Monte carlo dropout Uncertainty
Sarrera elektronikoa:	http://hdl.handle.net/10361/22153

Antzeko izenburuak

Analysis of uncertainty in different neural network structures using monte carlo dropout
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The Impact of Political Uncertainty on Asset Prices : The Case of the United Kingdom's EU Membership Referendum.
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Inflation, Uncertainty, and Growth in Colombia /
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An active-learning based training-schedule for biomedical image segmentation on deep neural networks
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Monte Carlo Simulation and Analysis in Modern Optical Tolerancing
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Monte Carlo Simulation and Analysis in Modern Optical Tolerancing
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The Drop-out problem in primary education : towards universalization of primary education in Asia and the Pacific, some case studies : China, India, Peninsular Malaysia, Socialist Republic of Viet Nam, Sri Lanka,Thailand.
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Identification and analysis of uncertainty in disaster risk reduction and climate change adaptation in South and Southeast Asia
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Preventing student drop out through supply chain management process: a focus on Directorate of Primary Education, Bangladesh
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Recent School Dropouts