Wildlife imaging shows that AI models aren't as smart as we think

Using AI to identify wildlife reveals a potential "transferability crisis," researchers say. Marketing for AI imaging systems ...

MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...
IEEE

Combine Meta-Learning With Feature Alignment for Cross-Domain Heterogeneous Hyperspectral Image Classification

Abstract: The scarcity of labeled samples results in the challenge of small sample size in hyperspectral image (HSI) classification. Transfer learning offers hope for solving this problem. In ...
IEEE

Cloud Adversarial Example Generation for Remote Sensing Image Classification

Abstract: Most existing adversarial attack methods for remote sensing images merely add adversarial perturbations or patches, resulting in visually unnatural modifications. Clouds are common ...
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 ...
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, ...
GitHub

Mean subtraction at inference time

Looking at the image classification example http://www.deepdetect.com/tutorials/imagenet-classifier/ using googlenet I am not seeing that the mean.binaryproto / mean.npy seems to be used for inference ...