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Showing 14 of 14 academic articles

A rapid fingerprint positioning method based on deep convolutional neural network for MIMO-OFDM systems

Chenlin He, Xiaojun Wang, Jiyu Jiao, Yuhua Huang et al. • Urban Lifeline (2024)

Abstract The combination of fingerprint positioning and 5G (the 5th Generation Mobile Communication Technology) offers broader application prospects for indoor positioning technology, but also brings challenges in real-time performance. In ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44285-024-00021-4

A review of convolutional neural networks in computer vision

Xia Zhao, Limin Wang, Yufei Zhang, Xuming Han et al. • Artificial Intelligence Review (2024)

Abstract In computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of dee...

OPENALEX cc-by DOI: https://doi.org/10.1007/s10462-024-10721-6

Deep Learning in Image Cytometry: A Review

Anindya Gupta, Philip John Harrison, Håkan Wieslander, Nicolas Pielawski et al. • Cytometry Part A (2018)

Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and ho...

OPENALEX cc-by-nc DOI: https://doi.org/10.1002/cyto.a.23701 PMC: 6590257

Face recognition with Bayesian convolutional networks for robust surveillance systems

Umara Zafar, Mubeen Ghafoor, Tehseen Zia, Ghufran Ahmed et al. • EURASIP Journal on Image and Video Processing (2019)

Abstract Recognition of facial images is one of the most challenging research issues in surveillance systems due to different problems including varying pose, expression, illumination, and resolution. The robustness of recognition method st...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13640-019-0406-y

Downscaling atmospheric chemistry simulations with physically consistent deep learning

A. Geiss, S. J. Silva, S. J. Silva, J. C. Hardin et al. • Geoscientific Model Development (2022)

Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrat...

DOAJ Open Access (DOAJ) DOI: 10.5194/gmd-15-6677-2022

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing (2018)

Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs10071119

TRIST: TREE RECOGNITION INTELLIGENT SYSTEM

Laura ONAC • Studia Universitatis Babes-Bolyai: Series Informatica (2019)

Plant recognition represents a challenging computer vision problem due to the great variations of shape and texture among plant organs, within the same species. This paper proposes a light-weight, but reasonably deep Convolutional Neural Ne...

DOAJ Open Access (DOAJ) DOI: 10.24193/subbi.2019.1.01

Adaptive habitat biogeography-based optimizer for optimizing deep CNN hyperparameters in image classification

Jiayun Xin, Mohammad Khishe, Diyar Qader Zeebaree, Laith Abualigah et al. • Heliyon (2024)

Deep Convolutional Neural Networks (DCNNs) have shown remarkable success in image classification tasks, but optimizing their hyperparameters can be challenging due to their complex structure. This paper develops the Adaptive Habitat Biogeog...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2024.e28147