An active-learning based training-schedule for biomedical image segmentation on deep neural networks

An active-learning based training-schedule for biomedical image segmentation on deep neural networks

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

Bibliografiset tiedot
Päätekijät:	Hassan, Mehadi, Das, Shemonto, Dipu, Shoaib Ahmed
Muut tekijät:	Majumdar, Mahbubul Alam
Aineistotyyppi:	Opinnäyte
Kieli:	en_US
Julkaistu:	Brac University 2021
Aiheet:	Active learning Deep learning Uncertainty metric Biomedical image segmentation
Linkit:	http://hdl.handle.net/10361/14809

Samankaltaisia teoksia

Image segmentation of X-Ray and optical images using U-Net/UNet++ based deep learning architecture
Tekijä: Sharma, Tanmoyee, et al.
Julkaistu: (2021)

Exploring deep features: deeper fully convolutional neural network for image segmentation
Tekijä: Kamran, Sharif Amit, et al.
Julkaistu: (2017)

3D Brain image segmentation using 3D tiled convolution neural networks
Tekijä: Haque, Md Mahibul, et al.
Julkaistu: (2024)

A comparison of deep learning U‐Net architectures for semantic segmentation on panoramic X-ray images
Tekijä: Bin Mushfiq, Rahil, et al.
Julkaistu: (2024)

Kidney Disease detection and classification from CT Images using Watershed Segmentation and Deep Learning.
Tekijä: Hossain, Mohammad Sakib, et al.
Julkaistu: (2023)

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

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

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

Transfer learning based industrial steel plates fault diagnosis using industrial fault signals
Tekijä: Mizan, Mubasshira, et al.
Julkaistu: (2024)

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

Impact of machine learning and deep learning on biomedical applications and healthcare industry
Tekijä: Kabir, Md Saif, et al.
Julkaistu: (2024)

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

Detecting Deepfake images using deep convolutional neural network
Tekijä: Dhar, Arpita, et al.
Julkaistu: (2022)

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

Structurally and semantically coherent deep image inpainting
Tekijä: Sami, Mirza Tanzim, et al.
Julkaistu: (2019)

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

Image processing and deep learning approach to evaluate earthquake resistance of urban buildings
Tekijä: Ahmed, Yasin, et al.
Julkaistu: (2018)

Automatic brain tumor segmentation using U-ResUNet chain model approach
Tekijä: Alam, Mohd Tanjeem, et al.
Julkaistu: (2022)

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

Detection and 3D visualization of Brain tumor using deep learning and polynomial interpolation
Tekijä: Tuhin, Md. Akram Hossan, et al.
Julkaistu: (2019)

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

An efficient deep learning approach to detect citrus leaves disease
Tekijä: Emon, Shaharear Hossain, et al.
Julkaistu: (2024)

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

Segmentation based Kidney Tumor Classification using Deep Neural Network
Tekijä: Mehedi, Md Humaion Kabir, et al.
Julkaistu: (2022)

Early stage detection and classification of colon cancer using deep learning and explainable AI on histopathological images
Tekijä: Hossain, Mainul, et al.
Julkaistu: (2022)

Customer segmentation using K-means
Tekijä: Mahdee, Nafis, et al.
Julkaistu: (2022)

Image recognition by deep learning
Tekijä: Mohiuddin, Karishma, et al.
Julkaistu: (2018)

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

Detection of coronary artery blockage at an early stage using effective deep learning technique
Tekijä: Promit, Tahmid Ashrafee, et al.
Julkaistu: (2023)

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

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

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

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

Deep learning based automated diagnosis of Ocular Toxoplasmosis in fundus images using convolutional neural network
Tekijä: Choudhury, Prionto Kumar, et al.
Julkaistu: (2024)

Tomato leaf disease detection using Resnet-50 and MobileNet Architecture
Tekijä: Tahamid, Abu
Julkaistu: (2021)

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

Leveraging deep learning algorithms for the timely detection of diseases in bean leaves
Tekijä: Fiona, Driciru, et al.
Julkaistu: (2024)

Leveraging unsupervised segmentation for semi-supervised renal calculi and carcinoma segmentation and classification
Tekijä: Faruk, Farhan, et al.
Julkaistu: (2024)

Classification of different magnetic structures from image data using deep neural networks
Tekijä: Ibn Hasib, Fahad, et al.
Julkaistu: (2023)

Image processing based human detection and social distancing measurements with monitoring via fine tuned deep learning and computer vision
Tekijä: Datta, Anurag, et al.
Julkaistu: (2022)