Keiller Nogueira

Lecturer

University of Stirling

United Kingdom

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Dr. Keiller Nogueira is a Lecturer at the University of Stirling, United Kingdom. His research focuses on data-centric machine learning, remote sensing, and image analysis, with recent publications addressing topics such as urban risk mapping for Aedes aegypti infestation and turbidity detection in hydroelectric reservoirs. He is dedicated to advancing methodologies in machine learning to enhance environmental monitoring and data interpretation.

Keiller Nogueira

Research Interests

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Articles (19)

Better, Not Just More: Data-centric machine learning for Earth observation

Automatic mapping of high-risk urban areas for Aedes aegypti infestation based on building facade image analysis.

Better, Not Just More: Data-centric machine learning for Earth observation

Better, Not Just More: Data-centric machine learning for Earth observation

Fully convolutional open set segmentation

Facing the Void: Overcoming Missing Data in Multi-View Imagery

GMM-IL: Image Classification Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes

NS-IL: Neuro-Symbolic Visual Question Answering Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes

Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs.

Facing the Void: Overcoming Missing Data in Multi-View Imagery

GMM-IL: Image Classification Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes

NS-IL: Neuro-Symbolic Visual Question Answering Using Incrementally Learnt, Independent Probabilistic Models for Small Sample Sizes

Noninvasive Low‐cost Method to Identify Armadillos' Burrows: A Machine Learning Approach

Semantic Segmentation of Tree-Canopy in Urban Environment with Pixel-Wise Deep Learning

Semantic segmentation of citrus-orchard using deep neural networks and multispectral UAV-based imagery

Benchmarking Anchor-Based and Anchor-Free State-of-the-Art Deep Learning Methods for Individual Tree Detection in RGB High-Resolution Images

AiRound and CV-BrCT: Novel Multiview Datasets for Scene Classification

An Introduction to Deep Morphological Networks

Facing Erosion Identification in Railway Lines Using Pixel-Wise Deep-Based Approaches

Collaborators (3)

Ribana Roscher

Kevin Swingler

Jefersson dos Santos

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