IEEE

A Robust Hybrid CNN+ViT Framework for Breast Cancer Classification Using Mammogram Images

Abstract: Breast cancer is the most frequent type of cancer largely experienced by women currently, although it could happen to men also. It appears when abnormal breast tissue cells grow rapidly and ...
IEEE

Comparison of Crop Image Classification Model Performance According to Image Augmentation Techniques

Abstract: Currently, the agricultural population is rapidly decreasing in Korea, and the aging population is getting worse. Therefore, the development of smart farm-related technologies is more ...
IEEE

Depression Classification Algorithm Based on Voice Signals Using MFCC and CNN Autoencoders

Abstract: Depression is a very common mental illness. In severe cases, it is a scary disease that can lead to suicide. Consequently, early diagnosis is essential because it can improve with ...
IEEE

Optimized CNN Architecture based on Mutant Particle Swarm Optimization and Opposition Based Learning for Image Classification

Abstract: Recent improvements in Convolution Neural Networks (CNN) have demonstrated extraordinary performance in solving real-world problems. However, the performance of CNN depends purely on its ...
IEEE

Hybrid CNN-LSTM Networks for Enhanced Lung Cancer Detection and Classification from CT Images

Abstract: In this paper, a hybrid deep learning model based on Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks are introduced for the automated detection of lung cancer ...
IEEE

Classification of Music Genres based on Machine Learning SVM and CNN

Abstract: This study aims to compare the performance of two classification methods—Support Vector Machine (SVM) and Convolutional Neural Network (CNN)—in identifying music genres based on audio data ...
IEEE

Can Language-Guided Unsupervised Adaptation Improve Medical Image Classification Using Unpaired Images and Texts?

Abstract: In medical image classification, supervised learning is challenging due to the scarcity of labeled medical images. To address this, we leverage the visual-textual alignment within ...
IEEE

Deep Learning Based - Brain Stroke Detection System on CT Images using CNN and Federated Learning (CNN-FL)

Abstract: Brain Stroke is one of the leading causes of death and long-term disability worldwide, with early detection being crucial for successful intervention and treatment. The use of deep learning ...
IEEE

Leukemia Classification Using CNN and VGG19 Architecture

Abstract: Leukemia, a severe kind of blood cancer marked by aberrant white blood cell proliferation, presents great difficulties for diagnosis and categorization. Effective treatment planning and ...
GitHub

image-classification-model

Computer vision model for detecting whether workers are wearing safety helmets in images. Useful for automated safety monitoring in industrial environments.
IEEE

Image Classification using Quantum Convolutional Neural Network (QCNN)

Abstract: Convolutional Neural Networks (CNNs) are extensively utilized for image classification due to their ability to exploit data correlations effectively. However, traditional CNNs encounter ...
IEEE

Breast Cancer Classification using Machine Learning Techniques with Explainable AI

Abstract: All the symptoms have been analyzed using several machine learning algorithms for diagnosing breast cancer. This paper utilizes the Breast Cancer Wisconsin (Diagnostic) data set to show how ...