• Assessing the Reliability of AI-Generated Medical Images: A Comparative Study with Real X-ray, CT, and MRI Scans 

  Islam, Md Muhetul (Daffodil International University, 2025-09-16)

  This paper presents a deep learning-based approach to differentiate between real medical images from AI-generated counterparts across X-ray, CT, and MRI images, addressing a critical challenge in healthcare diagnostics. ...
• Detection of Rose Leaf Diseases Using Deep Learning Methods 

  Lily, Anamika Hossain; Khan, Md. Walid Hassan (Daffodil International University, 2025-09-17)

  The study revolves around automated detection and classification of rose plant diseases, a central aspect of high-end agricultural technology. Disease in rose plants is a serious threat to sustainable plant growth because ...
• A Graph Neural Network Approach to Country-Level GDP Forecasting 

  Saha, Parthib (Daffodil International University, 2025-09-16)

  GDP forecasting is a major issue that requires accurate estimates on economic planning, policy formulation, trade policies and development objectives. Conventional statistical and machine learning models have delivered ...
• Bengali social media comments classification and toxicity detection using advanced machine learning algorithms 

  Rafin, Rayhan; Shibly, Mohammad Sohaib Islam (Daffodil International University, 2025-09-16)

  This project presents a system for classifying topics and sentiments from Bengali comments using both machine learning and deep learning algorithms. Detecting toxic behavior and hate speech is a primary usage of this ...
• An Approach to Improve the Efficiency of Deep Learning Framework for Skin Cancer Classification Utilizing Dermoscopy Images 

  Rahat, Md. Abdul Rabbi; Salman, Mehedi Hasan (Daffodil International University, 2025-09-17)

  Accurate identification and classification of skin cancer play an important role in early diagnosis, which is vital for reducing the mortality rate worldwide. However, challenges such as the variation in the appearances ...
• Comparative Evaluation of Machine Learning and Deep Learning Models for Mango Disease Detection 

  Alif, Hussain Muhammad (Daffodil International University, 2025-09-17)

  Mango is among the most valuable and popular fruits in Bangladesh and most other tropical nations in commercial terms. Mango farmers, however, experience serious losses in crop year after year because of numerous fruit ...
• Bengali Natural Language Processing: A Fine-Tuned Approach to Question Answering 

  Roy, Debashish; Noor, Md. Rafit Mostofa (Daffodil International University, 2025-09-16)

  Bengali is a native language spoken by more than 250 million people all over the world. Building a system that can understand human language and provide meaningful responses is really important in Natural Language Processing ...
• AI-Based Medical Diagnosis System for Disease Prediction Using Symtomps 

  Mahtab, Tahmid (Daffodil International University, 2025-09-17)

  Artificial Intelligence (AI) and Machine Learning (ML) have become a prominent part of changing the healthcare sector in the modern world. Machine learning algorithms assist in early detection of diseases by providing an ...
• Non-Invasive Blood Pressure Estimation Using Photoplethysmography and IoT-ML Integration 

  Sharif, Ridwan (Daffodil International University, 2025-09-17)

  The article examines the effectiveness of the cuffless blood pressure (BP) estimator based on photoplethysmography (PPG) signals, patient demographics, and machine learning. A prototype of IoT was created on the basis of ...
• TriVashi: A Multi-Stage System for Dialectal Speech Translation, Integrating Identification, Transcription, and Synthesis for Under-Resourced 

  Majumder, Salauddin; Surovi, Meheron Nesa (Daffodil International University, 2025-09-16)

  This increasing sophistication in natural language processing has in a paradoxical manner increased the digital divide and left thousands of lowresource languages and dialects underserved by technology. TriVashi is the ...
• TriVashi: A Multi-Stage System for Dialectal Speech Translation, Integrating Identification, Transcription, and Synthesis for Under-Resourced 

  Majumder, Salauddin; Surovi, Meheron Nesa (Daffodil International University, 2025-09-16)

  This increasing sophistication in natural language processing has in a paradoxical manner increased the digital divide and left thousands of lowresource languages and dialects underserved by technology. TriVashi is the ...
• Design and Implementation of an app Expense Tracker 

  Das, Robin; Biswas, Sourov (Daffodil International University, 2025-09-17)

  The "Expense Tracker" is a mobile app designed to make it easier and more convenient to keep track of your money. It's hard to keep track of where our money goes when we're busy. And occasionally we spend too much money. ...
• Decentralized Deep Learning for Rose Leaf Disease Detection: A Federated CNN Approach 

  Sowa, Pithila Mostofa; Islam, Syful (Daffodil International University, 2025-09-17)

  Rose is considered useful in agriculture and horticulture. Their leaves are however highly prone to illness such like black spot, mildew and mosaic virus. Such diseases may reduce the yield as well as quality. The conventional ...
• Deep Learning-Based Insect Pest Detection and Classification Using Vision Transformers and Knowledge Distillation for Sustainable Agriculture 

  Rifat, Anik Ahmed; Hossain, Md. Nirob (Daffodil International University, 2025-09-17)

  This study proves a new pest detection system at a deep level based on deep learning technology, which promotes the productivity of farmlands through real-time pest classification. Based on state-of-the-art Vision ...
• BongoFruits Bangladesh’s First Smart Fruit E-Commerce Platform 

  Rahman, Hafizur (Daffodil International University, 2025-09-16)

  The following project report explains the way Bongofruits was designed, constructed and tested. The new hybrid Bongofruits is a fusion of fruit e-commerce and educating people about money. The platform addresses two ...
• Decentralized Deep Learning for Rose Leaf Disease Detection: A Federated CNN Approach 

  Sowa, Pithila Mostofa; Islam, Syful (Daffodil International University, 2025-09-17)

  Rose is considered useful in agriculture and horticulture. Their leaves are however highly prone to illness such like black spot, mildew and mosaic virus. Such diseases may reduce the yield as well as quality. The conventional ...
• Deep Learning Approaches for Jute Leaf Disease Detection Using CNN Models Final Year Design Project 

  Biswas, Ushno Pabitro; Bulbul, Md. Aminul Islam (Daffodil International University, 2025-09-17)

  One of the major cash crops in Bangladesh is jute, which is crucial for the economy and supports millions of farmers. However, jute production often faces the risk of various leaf diseases, resulting in decreased yield and ...
• Detection of Tea Leaf Diseases Using Deep Transfer Learning 

  Athoi, Anzim Tasrif (Daffodil International University, 2025-09-17)

  One of the most serious plant diseases to the production of tea is the tea leaf disease. In the early stages, it often shows no visible symptoms, making early detection difficult until the infection spreads across the ...
• A Web-Based Book Recommendation System Implementing Machine Learning 

  Saad, Saadman (Daffodil International University, 2025-09-17)

  In this project, a personalized, precise book recommendation system is created based on the Book-Crossing dataset by using Truncated Singular Value Decomposition (SVD) of the matrices as a factorization on the dataset. ...
• Leaf Disease Detection in Bean and Eggplant Using Transfer Learning 

  Niloy, Saif Mahamud (Daffodil International University, 2025-09-17)

  In this work I developed a complete deep learning pipeline that classifies bean and eggplant leaf images into affected and healthy classes. I captured the source images myself using an iPhone and converted them to JPG ...

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