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Learning to decode linear codes using deep learning

Eliya Nachmani, Yair Be'ery, David Burshtein • Allerton Conference on Communication, Control, and Computing (2016)

A novel deep learning method for improving the belief propagation algorithm is proposed. The method generalizes the standard belief propagation algorithm by assigning weights to the edges of the Tanner graph. These edges are then trained us...

OPENALEX Open Access DOI: https://doi.org/10.1109/allerton.2016.7852251

Applications of Deep Learning and Reinforcement Learning to Biological Data

Mufti Mahmud, M. Shamim Kaiser, Amir Hussain, Stefano Vassanelli • IEEE Transactions on Neural Networks and Learning Systems (2018)

Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body...

OPENALEX Open Access DOI: https://doi.org/10.1109/tnnls.2018.2790388

Deep Learning-Driven Predictive Modelling for Optimizing Stingless Beekeeping Yields

Noor Hafizah Khairul Anuar, Mohd Amri Md Yunus, Muhammad Ariff Baharudin, Sallehuddin Ibrahim et al. • Journal of Computing Research and Innovation (2024)

Environmental factors like temperature, solar irradiance, and rain may influence the health and productivity of stingless bees. This paper aims to investigate the best approaches applied in meliponiculture to predict beehive health and prod...

DOAJ Open Access (DOAJ)

Automated Lung Sound Classification Using a Hybrid CNN-LSTM Network and Focal Loss Function

Georgios Petmezas, Grigorios-Aris Cheimariotis, Leandros Stefanopoulos, Bruno Rocha et al. • Sensors (2022)

Respiratory diseases constitute one of the leading causes of death worldwide and directly affect the patient’s quality of life. Early diagnosis and patient monitoring, which conventionally include lung auscultation, are essential for the ef...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22031232

A Survey on Deep Learning for Human Mobility

Massimiliano Luca, Gianni Barlacchi, Bruno Lepri, Luca Pappalardo • ACM Computing Surveys (2021)

The study of human mobility is crucial due to its impact on several aspects of our society, such as disease spreading, urban planning, well-being, pollution, and more. The proliferation of digital mobility data, such as phone records, GPS t...

OPENALEX Open Access DOI: https://doi.org/10.1145/3485125

An Integrated Method for River Water Level Recognition from Surveillance Images Using Convolution Neural Networks

Chen Chen, Rufei Fu, Xiaojian Ai, Chengbin Huang et al. • Remote Sensing (2022)

Water conservancy personnel usually need to know the water level by water gauge images in real-time and with an expected accuracy. However, accurately recognizing the water level from water gauge images is still a complex problem. This arti...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14236023

PharmaNet Deep: Real-Time Pharmaceutical Defect Detection Using Defect-Guided Feature Fusion and Uncertainty-Driven Inspection

Ajantha Vijayakumar, Joseph Abraham Sundar Koilraj, Muthaiah Rajappa • International Journal of Computational Intelligence Systems (2025)

Abstract Oral dosage forms are the most widely employed method of drug delivery in therapeutic treatments. However, the presence of visual defects in blister packages can adversely affect the drug's bioavailability and therapeutic efficacy,...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44196-025-00986-2

Ship Detection With SAR C-Band Satellite Images: A Systematic Review

Cyprien Alexandre, Rodolphe Devillers, David Mouillot, Raphael Seguin et al. • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2024)

Detecting and tracking ships remotely is now required in a wide range of contexts, from military security to illegal immigration control, as well as the management of fisheries and marine protected areas. Among the available methods, radar ...

DOAJ Open Access (DOAJ) DOI: 10.1109/JSTARS.2024.3437187

A Review of Machine Learning and Deep Learning Applications

Pramila P. Shinde, Seema Shah • International Conference on Computing Communication Control and automation (2018)

Machine learning is one of the fields in the modern computing world. A plenty of research has been undertaken to make machines intelligent. Learning is a natural human behavior which has been made an essential aspect of the machines as well...

OPENALEX DOI: https://doi.org/10.1109/iccubea.2018.8697857

Deep Learning With Edge Computing: A Review

Jiasi Chen, Xukan Ran • Proceedings of the IEEE (2019)

Deep learning is currently widely used in a variety of applications, including computer vision and natural language processing. End devices, such as smartphones and Internet-of-Things sensors, are generating data that need to be analyzed in...

OPENALEX DOI: https://doi.org/10.1109/jproc.2019.2921977

A Fast Inference Vision Transformer for Automatic Pavement Image Classification and Its Visual Interpretation Method

Yihan Chen, Xingyu Gu, Zhen Liu, Jia Liang • Remote Sensing (2022)

Traditional automatic pavement distress detection methods using convolutional neural networks (CNNs) require a great deal of time and resources for computing and are poor in terms of interpretability. Therefore, inspired by the successful a...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs14081877

Deep Learning Based Recommender System

Shuai Zhang, Lina Yao, Aixin Sun, Yi Tay • ACM Computing Surveys (2019)

With the growing volume of online information, recommender systems have been an effective strategy to overcome information overload. The utility of recommender systems cannot be overstated, given their widespread adoption in many web applic...

OPENALEX Open Access DOI: https://doi.org/10.1145/3285029