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Credit Card Fraud Detection with Machine Learning Classifiers
A comparative study that flags fraudulent card transactions in real time, training Logistic Regression, Decision Tree, Random Forest, and Neural Network models with balanced data preparation and a privacy-safe prediction flow.
Attention-Based Deep Learning for Breast Cancer MRI Classification
A deep learning pipeline that classifies benign vs malignant breast MRI scans using attention-enhanced DenseNet and VGG16, with visual explainability for clinical transparency.
Acute Lymphoblastic Leukemia Classification from Blood Smear Images
A deep learning study that classifies benign hematogones versus three ALL lymphoblast subtypes (Early Pre-B, Pre-B, Pro-B) from peripheral blood smear microscopy, comparing Modified AlexNet, VGG19, and DenseNet-121.
Lung Cancer Histopathology Classification with Basic CNN & DenseNet-121
A comparative study of Basic CNN, Modified AlexNet, VGG19, and DenseNet-121 on lung histopathology slides, classifying benign lung tissue, adenocarcinoma, and squamous cell carcinoma for digital pathology screening.
Real-Time Object Detection for Autonomous Driving with YOLOv8 & SS3D
A real-time object detection pipeline integrating YOLOv8 for 2D bounding boxes with Single Shot 3D (SS3D) for spatial visualization, detecting cars, pedestrians, and cyclists in driving scenes.
Bangla Braille Character Recognition with YOLOv8 & Faster R-CNN
An accessibility study that detects Bangla letters inside Braille patterns, comparing YOLOv8 and Faster R-CNN to help visually impaired learners read and write in their native language.
CNN Architecture Comparison for Image Classification
A deep learning benchmark of CNN architectures, from a custom Basic CNN to pretrained DenseNet-121, VGG-19, ResNet50, and Modified AlexNet, with transfer learning, augmentation, and full performance analysis.
Fake News Detection with SVM, 1D CNN & LSTM
A comparative study of Support Vector Machine, 1D Convolutional Neural Network, and LSTM models for classifying real vs fake news articles, trained on a public news corpus with TF-IDF features and deep text embeddings.
Heart Disease Analysis from Medical Reports with DistilRoBERTa & BETO
An NLP study that reads Colour Doppler Echocardiogram reports and classifies heart conditions, fine-tuning DistilBERT, DistilRoBERTa, and BETO transformers on hospital patient records for clinician use.
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