ProteoKnight: phage virion protein classification with CNN and uncertainty quantification

ProteoKnight: phage virion protein classification with CNN and uncertainty quantification

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2024.

Bibliografske podrobnosti
Main Authors:	Bhuiyan, Abir Ahammed, Neha, Samiha Afaf, Khan, Md. Ishrak
Drugi avtorji:	Rhaman, Md. Khalilur
Format:	Thesis
Jezik:	English
Izdano:	Brac University 2024
Teme:	Phage virion Deep learning DNA-walk Monte Carlo dropout Convolutional neural network (CNN) Neural networks (Computer science) Deep learning (Machine learning)
Online dostop:	http://hdl.handle.net/10361/22830

Podobne knjige/članki

Analysis of uncertainty in different neural network structures using Monte Carlo Dropout
od: Islam, Md. Farhadul, et al.
Izdano: (2024)

Analysis of uncertainty in different neural network structures using monte carlo dropout
od: Islam, Md. Farhadul, et al.
Izdano: (2024)

Analysing neural network models for detecting panic attacks with uncertainty analysis
od: Tahmid, Ahnaf, et al.
Izdano: (2024)

Classification of peripheral blood cell images using deep learning
od: Aadi, Oyshik Ahmed, et al.
Izdano: (2024)

Visual object classification from fMRI data
od: Newaz, Syed Mishar, et al.
Izdano: (2022)

Analysis of transformer and CNN based approaches for classifying renal abnormality from image data
od: Reza, S. M. Mushfiq, et al.
Izdano: (2024)

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

Deep learning-based hybrid multi-task model for adrenocortical carcinoma segmentation and classification
od: Datta, Nirjhor, et al.
Izdano: (2024)

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

An efficient deep learning approach to detect skin cancer using image data
od: Chowdhury, Yaser Al Rahman, et al.
Izdano: (2023)

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

Sequential Monte Carlo methods in practice /
Izdano: (2001)

An efficient ML approach to detect brain tumor using MRI images
od: Muktadir, MD. Arafat, et al.
Izdano: (2024)

Early Schizophrenia Diagnosis with 3D Convolutional Neural Network
od: Ashraf, S.M. Nabil, et al.
Izdano: (2021)

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

Visual object recognition using deep convolutional neural network
od: Ahmed, Sabbir
Izdano: (2017)

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

Diabetic retinopathy detection and classification by using deep learning
od: Hossain, Shahriar, et al.
Izdano: (2022)

Plant leaf disease identification
od: Hasan Mahin, Mohammad Rakibul, et al.
Izdano: (2024)

Efficient image processing and machine learning approach for predicting retinal diseases
od: Hasib, Mehadi Hasan, et al.
Izdano: (2021)

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

An eﬃcient deep learning approach for detecting lung disease from chest X-ray images using transfer learning and ensemble modeling
od: Sagor, Mostofa Kamal, et al.
Izdano: (2021)

BanglaBait: using transformers, neural networks & statistical classifiers to detect clickbaits in New Bangla Clickbait Dataset
od: Mahtab, Motahar, et al.
Izdano: (2022)

Detection of handwritten text using convolutional neural network
od: Jasim, Rabib Bin, et al.
Izdano: (2024)

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

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

Autonomous fault diagnosis of commercially available PV modules using high-end deep learning frameworks
od: Tasawar, Ihtyaz Kader, et al.
Izdano: (2021)

Cancer classification using deep learning from medical image data
od: Monir, Raiyan Janik, et al.
Izdano: (2022)

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

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

Analysis of real-time hostile activitiy detection from spatiotemporal features using time distributed deep convolutional neural networks, recurrent neural networks and attention-based mechanisms
od: Siddique, Labib Ahmed, et al.
Izdano: (2022)

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

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

Fighting depression: psychological approaches among Bangladeshi university students
od: Sen, Sanjib Kumar, et al.
Izdano: (2022)

Real time action recognition from video footage
od: Apon, Tasnim Sakib, et al.
Izdano: (2021)

Classification of respiratory diseases and COVID-19 from respiratory and cough sound using deep learning techniques
od: Ahasan, Md. Mubtasim, et al.
Izdano: (2022)

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

Pneumonia Disease detection using the convolutional neural network
od: Ashrafee, Md. Iftid, et al.
Izdano: (2024)

Deep Learning based Medicinal Plants Leaf Recognition
od: Mahalanabish, Tonusri
Izdano: (2023)

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