Abstract: File fragment classification is an important step in digital forensics. The most popular method is based on traditional machine learning by extracting features like N-gram, Shannon entropy ...

Abstract: Deep learning has achieved great successes in conventional computer vision tasks. In this paper, we exploit deep learning techniques to address the hyperspectral image classification problem ...

This repository presents an image-based malware classification system developed. The proposed approach transforms malware binaries into grayscale images and applies Convolutional Neural Networks (CNNs ...

Customer stories Events & webinars Ebooks & reports Business insights GitHub Skills ...

Deep learning has transformed remote sensing, driving state-of-the-art results in land use and land cover classification, ...

Artificial intelligence can now generate images that are virtually indistinguishable from real ones. Researchers at the Fraunhofer Institute of Optronics, System Technologies and Image Exploitation ...

Retinal imaging and deep learning (DL) may support scalable screening, but deployment requires evidence on pooled performance. This is important because missed neovascular disease may delay treatment, ...

In this interview, AZoLife Sciences speaks with Boyd Butler, a microscopy and high-content screening expert at Molecular ...

At Carnegie Mellon University’s Next Manufacturing Center, researchers have developed an off-axial imaging system to capture ...

Cut through AI jargon with this practical AI glossary. Learn essential AI terms like LLMs, hallucination, tokens, and more in plain English. Understand AI confidently.