Prostate cancer detection using deep learning neural network with transfer learning approach

Prostate cancer detection using deep learning neural network with transfer learning approach

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2021.

Bibliografski detalji
Glavni autori:	Badhon, Ariful Islam Mahmud, Hasan, Md. Sadman, Haque, Md. Samiul, Pranto, Md. Shafayat Hossain, Ghosh, Saurav
Daljnji autori:	Alam, Md. Golam Rabiul
Format:	Disertacija
Jezik:	English
Izdano:	Brac University 2022
Teme:	Prostate cancer Deep learning ImageNet Transfer learning VGG16 Image classification Machine learning classifier Cognitive learning theory (Deep learning) Neural networks (Computer science) Machine learning
Online pristup:	http://hdl.handle.net/10361/16454

Similar Items

A modern technique to detect potholes by Computer Vision and Deep Learning
od: Saif, Muntasir Mahmud, i dr.
Izdano: (2023)

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

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

Image processing and deep learning approach to evaluate earthquake resistance of urban buildings
od: Ahmed, Yasin, i dr.
Izdano: (2018)

Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
od: Choudhury, Prionto Kumar, i dr.
Izdano: (2024)

Damaged road detection using Image Processing and Deep Learning
od: Swadesh, Shimran Mahbub, i dr.
Izdano: (2022)

Transfer learning based industrial steel plates fault diagnosis using industrial fault signals
od: Mizan, Mubasshira, i dr.
Izdano: (2024)

Deep learning-based real-time pothole detection for avoiding road accident
od: Basher, Rafsan, i dr.
Izdano: (2022)

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
od: Sharma, Tanmoyee, i dr.
Izdano: (2021)

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

An active-learning based training-schedule for biomedical image segmentation on deep neural networks
od: Hassan, Mehadi, i dr.
Izdano: (2021)

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

Implementing machine learning techniques to forecast floods In Bangladesh based on historical data
od: Toufique, S.M, i dr.
Izdano: (2024)

Analysis of deep learning models on low-light pest detection
od: Irtiza, Md. Samin, i dr.
Izdano: (2023)

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

Image recognition by deep learning
od: Mohiuddin, Karishma, i dr.
Izdano: (2018)

Financial factors analysis for acquisition premium and anticipation using extreme gradient boosting and deep recurrent neural network
od: Rayhan, Mohammad, i dr.
Izdano: (2020)

Real-time mastitis detection in livestock using deep learning and machine learning leveraging edge devices
od: Ghosh, Kawshik Kumar, i dr.
Izdano: (2023)

RetinalNet-500: a newly developed CNN model for eye disease detection
od: Toki, Sadikul Alim, i dr.
Izdano: (2023)

An implementation and analysis of deep learning models for the detection of wheat diseases
od: Zubair, Ahmad, i dr.
Izdano: (2024)

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

Predicting crime using deep learning
od: Shihab, Muhammad Nafees, i dr.
Izdano: (2024)

Yoga posture recognition using the deep learning process
od: Islam, Abidul, i dr.
Izdano: (2023)

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

Deep learning approaches for Bengali cyberbullying cetection on social media: a comparative study of BiLSTM, BiGRU and BERT models
od: Fahim, Kaji Mehedi Hasan, i dr.
Izdano: (2024)

Non-clinical Covid19 diagnosis on CT-scan, Chest X-ray, and respiratory patterns using deep-learning and signal processing
od: Tasnim, Sadia, i dr.
Izdano: (2023)

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

Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
od: Fiona, Driciru, i dr.
Izdano: (2024)

Detection of acute Lymphocytic Leukemia (ALL) and its type by image processing and machine learning
od: Chowdhury, Himadri, i dr.
Izdano: (2019)

Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision
od: Datta, Anurag, i dr.
Izdano: (2022)

Application of CNN based architectures in detection of distracted drivers
od: Arafin, Irfana, i dr.
Izdano: (2023)

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

Real-time foul detection in football matches using machine learning techniques
od: Siddiqui, Bishal Sadi, i dr.
Izdano: (2024)

Deep Learning based Bangla Voice to Braille Character Conversion System
od: Iqbal, Syed Bayes, i dr.
Izdano: (2022)

An efficient deep learning approach to detect citrus leaves disease
od: Emon, Shaharear Hossain, i dr.
Izdano: (2024)

Predicting the outcome of purchasing a hotel package to assist policymakers using machine learning
od: Islam, Zahedul, i dr.
Izdano: (2023)

Recall-Net: A CNN-based Model for Four-class Classification of Alzheimer’s Disease
od: Hasan, M. M. Kamrul, i dr.
Izdano: (2022)

Sentiment analysis on Bangladesh airlines review data using machine learning
od: Hasib, Khan Md.
Izdano: (2022)

Multimodal human detection in disaster situations using deep learning & artificial intelligence
od: Rafat, Md. Tasbi, i dr.
Izdano: (2023)

Cassava leaf disease classification using deep learning and convolutional neural network ensemble
od: Shahriar, Hasan, i dr.
Izdano: (2022)