A hybrid FL-Enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN

A hybrid FL-Enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN

Pokaż inne wersje (1)

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2022.

Opis bibliograficzny
Główni autorzy:	Chowdhury, Asif Hasan, Islam, Md. Fahim, Riad, M Ragib Anjum, Hashem, Faiyaz Bin
Kolejni autorzy:	Alam, Md. Golam Rabiul
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2023
Hasła przedmiotowe:	AI VGG19 Inception V3 DenseNet201 SWIN transformer Federated learning Privacy Medical informatics Cognitive science
Dostęp online:	http://hdl.handle.net/10361/21851

Podobne zapisy

A hybrid FL-enabled ensemble approach for lung disease diagnosis leveraging fusion of SWIN transformer and CNN
od: Chowdhury, Asif Hasan, i wsp.
Wydane: (2023)

Detection of coronary artery blockage at an early stage using effective deep learning technique
od: Promit, Tahmid Ashrafee, i wsp.
Wydane: (2023)

Prediction of glaucoma from fundus images leveraging transfer learning in deep neural network
od: Ismail, Sayem Mohammad, i wsp.
Wydane: (2021)

MalFam: a comprehensive study on malware families with state-of-the-art CNN architectures with classifications and XAI
od: Haque, Abid Hossain, i wsp.
Wydane: (2024)

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

Towards devising an effective and reliable means of fish detection and classification through the exploration of various deep learning algorithms
od: Farhan, Rafid, i wsp.
Wydane: (2024)

EAI4CC: deciphering lung and colon cancer categorization within a federated learning framework harnessing the power of explainable artificial intelligence
od: Mim, Ankhi Akter, i wsp.
Wydane: (2024)

Diabetic retinopathy detection and classification by using deep learning
od: Hossain, Shahriar, i wsp.
Wydane: (2022)

A deep learning approach towards soft biometrics attributes prediction using CNN
od: Kibria, Maharab, i wsp.
Wydane: (2022)

Enhancing Monkeypox diagnosis: a machine learning approach for skin lession classification
od: Nazmee, Namirah, i wsp.
Wydane: (2024)

Citrus leaf disease detection by image processing
od: Chowdhury, Mahir Faisal, i wsp.
Wydane: (2024)

Thoracic complication detection on chest X-rays using deep learning
od: Ratul, Rizwanul Hoque, i wsp.
Wydane: (2021)

Detection of intracranial hemorrhage on CT scan images using convolutional neural network
od: Rahman, Afridi Ibn, i wsp.
Wydane: (2022)

Anomalous behavior detection using Spatio temporal Feature and 3D CNN model for Surveillance
od: Nahar, Jannatun, i wsp.
Wydane: (2022)

An efficient deep learning approach to detect retinal disease using optical coherence tomographic images
od: Khan, Farhan Sakib, i wsp.
Wydane: (2022)

Owning up
od: Adams, Katherine

Analyzing security threats and mitigation techniques for fog computing in IoT-enabled smart cities
od: Emon, Sheikh Sadi, i wsp.
Wydane: (2024)

Gender classification in Bangla language using deep learning-based voice analysis
od: Hakim, Talukder Juhaer, i wsp.
Wydane: (2024)

Analyzing user data privacy in android mobile OS
od: Miah, Abdul Momen, i wsp.
Wydane: (2023)

An interpretable deep learning approach to detect Alzheimer using MRI images
od: Oni, Farhan Anzum, i wsp.
Wydane: (2023)

Personalization in federated recommendation system using SVD++ with explainability
od: Patwary, Kabbya Kantam, i wsp.
Wydane: (2022)

Security in computing /
od: Pfleeger, Charles P., 1948-
Wydane: (2003)

Who knows : safeguarding your privacy in a networked world /
od: Cavoukian, Ann
Wydane: (1997)

Evaluating the effectiveness of CNN-based models for diabetic retinopathy detection
od: Niaz, H.M, i wsp.
Wydane: (2024)

Skin lesion classification using different CNN models
od: Oli, Md. Yahea Sultan
Wydane: (2023)

Multiclass emotion classification by using Spectrogram image analysis: A CNN-XGBoost fusion approach
od: Esha, Ishraq Ahmed, i wsp.
Wydane: (2023)

DenseNet based skin lesion classification and melanoma detection
od: Munaf, Arifuzzaman, i wsp.
Wydane: (2021)

Identifying brain abnormalities using image processing and CNN models
od: Talukder, Ismat Shehrin, i wsp.
Wydane: (2021)

An efficient deep learning approach to predict heart failure from image data using ejection fraction
od: Tanvir, Nazmul Karim, i wsp.
Wydane: (2023)

Advanced artificial intelligence self balanced robot for home security
od: Shourove, MD. Niaz Sharif, i wsp.
Wydane: (2018)

Law for computer scientists and other folk /
od: Hildebrandt, Mireille

Translational informatics in smart healthcare /
Wydane: (2017)

Semantic segmentation with attention dense U-net for lung extraction from X-ray images
od: Auvy, Akib Al Mahmud, i wsp.
Wydane: (2023)

CancerCare: A reliable and secured self-supervising and interactive system using deep learning
od: Khisa, Pushpakali, i wsp.
Wydane: (2024)

The impact of proper information management and data storage for long term decision-making business process and risk mitigation at MNCs – A perspective from Chevron Bangladesh
od: Sumaya
Wydane: (2024)

Comparative analysis between Inception-v3 and other learning systems using facial expressions detection
od: Nivrito, AKM, i wsp.
Wydane: (2016)

Covid-19 infected lung detection using machine learning
od: Islam, Md. Muntaha, i wsp.
Wydane: (2022)

The Salome Ensemble
od: Ginsberg

Two dimensional convolutional neural network CNN approach for detection of Bangla sign language
od: Nag, Pollock, i wsp.
Wydane: (2023)

Implementation of real-time learning on homomorphically encrypted visual inputs
od: Bhuiyan, Emtiaz MD Tafsir, i wsp.
Wydane: (2021)