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Showing 9 of 29 academic articles

Deep Learning in Microscopy Image Analysis: A Survey

Fuyong Xing, Yuanpu Xie, Hai Su, Fujun Liu et al. • IEEE Transactions on Neural Networks and Learning Systems (2017)

Computerized microscopy image analysis plays an important role in computer aided diagnosis and prognosis. Machine learning techniques have powered many aspects of medical investigation and clinical practice. Recently, deep learning is emerg...

OPENALEX DOI: https://doi.org/10.1109/tnnls.2017.2766168

A Comprehensive Survey on Community Detection With Deep Learning

Xing Su, Shan Xue, Fanzhen Liu, Jia Wu et al. • IEEE Transactions on Neural Networks and Learning Systems (2022)

Detecting a community in a network is a matter of discerning the distinct features and connections of a group of members that are different from those in other communities. The ability to do this is of great significance in network analysis...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2021.3137396

Deep Learning on Graphs: A Survey

Ziwei Zhang, Peng Cui, Wenwu Zhu • IEEE Transactions on Knowledge and Data Engineering (2020)

Deep learning has been shown to be successful in a number of domains, ranging from acoustics, images, to natural language processing. However, applying deep learning to the ubiquitous graph data is non-trivial because of the unique characte...

OPENALEX Open Access DOI: https://doi.org/10.1109/tkde.2020.2981333

Deep Learning in Drug Discovery

Erik Gawehn, Jan A. Hiss, Gisbert Schneider • Molecular Informatics (2015)

Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical ...

OPENALEX DOI: https://doi.org/10.1002/minf.201501008

Deep Learning

Ian Goodfellow, Yoshua Bengio, Aaron C. Courville • The MIT Press eBooks (2016)

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...

OPENALEX DOI: https://doi.org/10.1016/b978-0-12-804291-5.00010-6

Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction

Alejandro Casallas, Camila Jiménez-Saenz, Victor Torres, Miguel Quirama-Aguilar et al. • Sensors (2022)

Throughout the years, wildfires have negatively impacted ecological systems and urban areas. Hence, reinforcing territorial risk management strategies against wildfires is essential. In this study, we built an early alert system (EAS) with ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22228790

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

Probabilistic daily runoff forecasting in high-altitude cold regions using a hybrid model combining DBO and transformer variants

Qiying Yu, Wenzhong Li, Yungang Bai, Zhenlin Lu et al. • Journal of Hydrology: Regional Studies (2025)

Study Area: The Tailan River Basin in the Aksu region and the Yulong Kashi River in the Hotan River Basin of Xinjiang are located at respective geographical coordinates of 80°21'44'' to 81°10'14'' E, 40°41'41'' to 42°15'13'' N, and 77.25° t...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ejrh.2025.102311