Cargando…
Optimisation of Deep Learning Small-Object Detectors with Novel Explainable Verification
In this paper, we present a novel methodology based on machine learning for identifying the most appropriate from a set of available state-of-the-art object detectors for a given application. Our particular interest is to develop a road map for identifying verifiably optimal selections, especially f...
Autores principales: | Mohamed, Elhassan, Sirlantzis, Konstantinos, Howells, Gareth, Hoque, Sanaul |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330345/ https://www.ncbi.nlm.nih.gov/pubmed/35898097 http://dx.doi.org/10.3390/s22155596 |
Ejemplares similares
-
A pixel-wise annotated dataset of small overlooked indoor objects for semantic segmentation applications.
por: Mohamed, Elhassan, et al.
Publicado: (2022) -
An annotated water-filled, and dry potholes dataset for deep learning applications
por: Dib, Jihad, et al.
Publicado: (2023) -
An Attention-Guided Framework for Explainable Biometric Presentation Attack Detection
por: Pan, Shi, et al.
Publicado: (2022) -
Effect of Gait Speed on Trajectory Prediction Using Deep Learning Models for Exoskeleton Applications
por: Kolaghassi, Rania, et al.
Publicado: (2023) -
Performance of Deep Learning Models in Forecasting Gait Trajectories of Children with Neurological Disorders
por: Kolaghassi, Rania, et al.
Publicado: (2022)