Beijing, Feb. 06, 2026 (GLOBE NEWSWIRE) -- WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...

President Donald Trump seemed to rule out using force to take Greenland in his speech at Davos. Meanwhile, Trump is set to meet with Ukraine’s President Volodymyr Zelensky at the summit. The legal ...

+This project focuses on building a Convolutional Neural Network (CNN) using Keras (TensorFlow backend) to classify images into two categories: Dog and Cat. + +The objective is to learn meaningful ...

In this video, we will implement Image Classification using CNN Keras. We will build a Cat or Dog Classification model using CNN Keras. Keras is a free and open-source high-level API used for neural ...

Abstract: Histopathology is crucial for diagnosing many diseases as early as possible, especially cancer. It involves looking at tissue samples under a microscope and checking if something is wrong.

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

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...

Electroencephalogram (EEG) signal analysis plays a vital role in diagnosing and monitoring alcoholism, where accurate classification of individuals into alcoholic and control groups is essential.

• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).