IEEE

3D CT Liver Images Lesion Extraction and Classification for Using 3D-CNN with GLRLM

Abstract: The imaging technique known as computed tomography (CT) is often considered to be the most reliable way for non-invasive diagnosis. Through the use of three-dimensional (3D) computed ...
GitHub

Pull requests: eirenemichellatjhan/Pharmaceutical-Drug-Image-Classification-using-CNN-and-Transfer-Learning_Deep-Learning

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
Business Insider

MicroCloud Hologram Inc. Releases Hybrid Quantum-Classical Convolutional Neural Network, Achieving New Breakthrough in MNIST Multi-Class Classification

SHENZHEN, China, Oct. 24, 2025 (GLOBE NEWSWIRE) -- MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a Quantum Convolutional Neural Network ...
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 ...
GitHub

[FEAT]: Part 2.2: Build baseline MNIST CNN

Build, train, and evaluate a Convolutional Neural Network (CNN) for classifying the MNIST handwritten digits dataset using either TensorFlow or PyTorch. The primary goal is to create a model that ...