In tests on standard image classification datasets (CIFAR-100, TinyImageNet), Lp-Convolution significantly improved accuracy on both classic models like AlexNet and modern architectures like RepLKNet.

For unknown reasons, the human brain distinctly separates the handling of images of living things from images of non-living things, processing each image type in a different area of the brain. For ...

Expectations lead to less but more efficient processing in the human brain. ScienceDaily . Retrieved June 2, 2025 from www.sciencedaily.com / releases / 2012 / 07 / 120726094506.htm ...

Image processing is at the helm of the technical revolution that is being called Industry 4.0, laying the framework for new technologies in image data processing and object recognition. Image ...

Brain tumour classification: The neural network classifies tumour type based on its image characteristics in the MRI scan. The colour maps show which pixels led to a correct prediction, with warmer ...

The human brain can achieve the remarkable feat of processing an image seen for just 13 milliseconds, scientists have found. This lightning speed obliterates the previous record speed of 100 ...

Brain tumors can be easily detected by magnetic resonance imaging (MRI), but their exact classification is difficult in this way. Yet that's precisely what's crucial for choosing the best possible ...