Abstract: Graph Neural Networks (GNNs) are rapidly becoming essential tools in deep learning, but their effectiveness when applied to images is often limited by challenges in graph representation.

Abstract: Fine-grained image classification (FGIC) remains a challenging task due to subtle inter-class differences and significant intra-class variations, particularly under limited training data.

Abstract: Medical image classification has been significantly improved by Convolutional Neural Networks (CNN), enabling efficient and accurate diagnosis, especially in detecting brain tumors. Despite ...

A CNN insider reportedly issues a “wake-up call” to Kaitlan Collins as her presence at an exclusive no-journalists party sparks backlash and questions about her image. Samuel Alito raises question ...

Abstract: Feature representation is crucial for hyperspectral image (HSI) classification. However, existing convolutional neural network (CNN)-based methods are limited by the convolution kernel and ...

Abstract: Aerial image classification plays a vital role in applications such as building footprint extraction, water/soil analysis, 3D reconstruction. Accurate classification enables timely ...

The chattering class is consumed this morning by two interlocking questions: who will actually run CNN once the Paramount-Warner Bros. Discovery deal closes, and whether Bari Weiss is up to the job.

After Russia invaded Ukraine in 2022, social media was littered with crude fakes that were presented as fresh images of the war but were either photoshopped phonies or mislabeled clips taken from ...