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Showing 5 of 65 academic articles

CG-DINO: Improved Network for Small Object Detection in Uncrewed Aerial Vehicle Imagery Based on DINO

Jian Liu, Pei Niu, Yihui Jiang, Zilong Zhao et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2026)

Object detection in uncrewed aerial vehicle (UAV) acquired images remains a challenging task due to extreme scale variation, dense object layouts, and complex backgrounds, etc. Although convolutional neural networks (CNNs), transformers, an...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2026.3729713

Explainable and reliable kidney CT image classification using self-supervised DeiT-Tiny transformer

Sai Sri Hemantha Konala, Srinivas Koppu • Frontiers in Medicine (2026)

IntroductionKidney-related disorders are one of the global health concerns that require timely detection to prevent severe health complications. The use of computed tomography (CT) images for accurate classification of kidney diseases is im...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2026.1893419

Deep learning for neuroimaging: a validation study

Sergey Plis, Devon Hjelm, Ruslan Salakhutdinov, Elena A. Allen et al. • Frontiers in Neuroscience (2014)

Deep learning methods have recently made notable advances in the tasks of classification and representation learning. These tasks are important for brain imaging and neuroscience discovery, making the methods attractive for porting to a neu...

OPENALEX cc-by DOI: https://doi.org/10.3389/fnins.2014.00229 PMC: 4138493

Comparing Clinical Metadata Fusion Strategies for Diabetic and Hypertensive Retinopathy Classification

Vinicius de Carvalho Rispoli, Alan Müller, Weverson Garcia Medeiros, Marília Miranda Forte Gomes et al. • Machine Learning and Knowledge Extraction (2026)

Structured clinical variables may complement fundus photographs, but the most appropriate point at which to integrate them into a retinal foundation model remains uncertain. This study compares an image-only baseline with three strategies f...

DOAJ Open Access (DOAJ) DOI: 10.3390/make8100299

Development of a BIM-based AI-driven matching tool for LCA datasets

Dino Petrosa, Pamela Haverkamp, Jana Gerta Backes, David Crampen et al. • Discover Sustainability (2025)

Abstract The construction sector significantly contributes to environmental issues and often relies on Life Cycle Assessment (LCA) for the quantification and optimization of its environmental impacts. One of the most time- and labour-intens...

DOAJ Open Access (DOAJ) DOI: 10.1007/s43621-025-02203-8