How to spot an AI image: 6 telltale signs it's fake - and my go-to free detectors

So, how can you spot an AI image? Here are six signs for spotting the fakes, plus my favorite free AI image detector.
Infectious Disease Advisor

ATS/ERS Issue Interstitial Pneumonia Classification Update

The ATS/ERS 2025 statement on interstitial pneumonia classification updates the 2013 statement, with insights on secondary ...
IEEE

SemiBaCon: Semi-Supervised Balanced Contrastive Learning for Multimodal Remote Sensing Image Classification

Abstract: The limited availability of annotated training data significantly constrains the classification accuracy of hyperspectral image (HSI) and LiDAR fusion approaches. Although contrastive ...
GitHub

Visual Comfort Analysis Based on Urban 3D Models and Street View Images—Taking Nanshan District of Shenzhen City as an Example

With the continuous advancement of urbanization, high-rise buildings are increasingly blocking the sky, natural green spaces are diminishing, and the visible sky is shrinking. Consequently, people's ...
GitHub

Image classification training convert to onnx file format

I've been doing experiments with the C# image classification examples, and I've been struggling trying to modify the sample to save an ONNX file without success, since it gives me the usual "The ...
Frontiers

Fine-grained image classification using the MogaNet network and a multi-level gating mechanism

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 ...
Scientific Research Publishing

A Wavelet-Based Two-Stage Vision Transformer Model for Histological Subtypes Classification of Lung Cancers on CT Images ()

1 Faculty of Informatics, The University of Fukuchiyama, Kyoto, Japan. 2 School of Radiological Technology, Gunma Prefectural College of Health Sciences, Gunma, Japan. 3 School of Health Sciences, ...
Frontiers

GLN-LRF: global learning network based on large receptive fields for hyperspectral image classification

Deep learning has been widely applied to high-dimensional hyperspectral image classification and has achieved significant improvements in classification accuracy. However, most current hyperspectral ...