Abstract: This paper rethinks image histogram matching (HM) and proposes a differentiable and parametric HM preprocessing for a downstream classifier. Convolutional neural networks have demonstrated ...
Abstract: Breast cancer remains a leading cause of mortality among women worldwide, emphasizing the critical importance of early and accurate detection in improving patient outcomes and treatment ...
Abstract: Accurate classification of otoscopic ear images is crucial for early diagnosis of ear pathologies such as Chronic Otitis Media, Earwax Plug, and Myringosclerosis. In this study, we propose a ...
(CNN) — Video and images showing an armed, masked individual outside the Tucson, Arizona, home of Nancy Guthrie have given new life to the search for the 84-year-old – and may offer investigators ...
Abstract: This letter proposes KAN-based multispectral image super-resolution method (KMSR), a novel deep learning framework for multispectral image (MSI) super-resolution (SR) that integrates ...
Abstract: Hyperspectral image classification is a fundamental task in remote sensing with broad applications in precision agriculture, environmental monitoring, and related fields. However, existing ...
Former Air Force Secretary reacts to OpenAI announcing it made a deal with the Pentagon amid Anthropic fued ...
Abstract: Various lesions in different body parts have different sizes and, in particular, different representations, which leads to great challenges for medical image classification tasks. To avoid ...
Abstract: Document image classification has a significant difficulty for the retrieval of digital documents and systems management in recent years. The main goal of this study is to investigate the ...
This project presents a comprehensive deep learning study focused on Convolutional Neural Network (CNN) architecture experimentation and model interpretability using the Mini-ImageNet dataset. The ...
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