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

A futuristic AI symbol hovers effortlessly, adorned with a bright red and white Christmas hat, blending holiday cheer with cutting-edge technology. The minimalist background accentuates the playful ...

Sign up for the Slatest to get the most insightful analysis, criticism, and advice out there, delivered to your inbox daily. By mid-October, the Democrats’ chances ...

Despite calling it a “hoax” President Donald Trump gave a speech on how he’ll address the affordability crisis. Miami elects its first Democrat mayor in nearly 30 years. We have more details on the ...

When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. This information might be about you, your preferences or your device and is mostly used ...

Tides have changed with the Gemini 3 update, bringing Nano Banana Pro image generation to a wider range of users. The images are so realistic that Google provides an extension that detects images with ...

Nov. 18 (UPI) --President Donald Trump's lawsuit against CNN for using the phrase "The Big Lie" was rejected by a federal appeals court. Trump was trying to revive the $475 million suit against the ...

Google's Gemini 2.5 Flash AI image generation model was known as Nano Banana during pre-release testing when it first went viral. The name stuck after Google released Nano Banana in late August. The ...

Kara Alaimo is a professor of communication at Fairleigh Dickinson University. Her book “Over the Influence: Why Social Media Is Toxic for Women and Girls — And How We Can Take It Back” was published ...

1 School of Electronics and Electrical Engineering, Zhengzhou University of Science and Technology, Zhengzhou, China 2 Department of Mechanical and Electrical Engineering, Henan Vocational College of ...

• 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).