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A review on deep learning in medical image analysis

S. Suganyadevi, V. Seethalakshmi, K. Balasamy • International Journal of Multimedia Information Retrieval (2021)

Ongoing improvements in AI, particularly concerning deep learning techniques, are assisting to identify, classify, and quantify patterns in clinical images. Deep learning is the quickest developing field in artificial intelligence and is ef...

OPENALEX other-oa DOI: https://doi.org/10.1007/s13735-021-00218-1 PMC: 8417661

Combining the YOLOv4 Deep Learning Model with UAV Imagery Processing Technology in the Extraction and Quantization of Cracks in Bridges

Szu-Pyng Kao, Yung-Chen Chang, Feng-Liang Wang • Sensors (2023)

Bridges are often at risk due to the effects of natural disasters, such as earthquakes and typhoons. Bridge inspection assessments normally focus on cracks. However, numerous concrete structures with cracked surfaces are highly elevated or ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052572

A novel agricultural commodity price prediction model integrating deep learning and enhanced swarm intelligence algorithm.

Kaixuan Sun, Qi Yao, Yanhui Li • PLoS ONE (2025)

The volatility of agricultural commodity prices significantly affects market stability and financial market dynamics, especially during periods of economic uncertainty and global shocks. Accurate price prediction, however, remains challengi...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0337103

CAMELON: A System for Crime Metadata Extraction and Spatiotemporal Visualization From Online News Articles

Siripen Pongpaichet, Boonyapat Sukosit, Chitchaya Duangtanawat, Jiramed Jamjongdamrongkit et al. • IEEE Access (2024)

Crimes result in not only loss to individuals but also hinder national economic growth. While crime rates have been reported to decrease in developed countries, underdeveloped and developing nations still suffer from prevalent crimes, espec...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3363879

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 Steering Angle Prediction in Autonomous Vehicles

Usman Manzo Gidado, Haruna Chiroma, Nahla Aljojo, Saidu Abubakar et al. • IEEE Access (2020)

Steering angle prediction is critical in the control of Autonomous Vehicles (AVs) and has attracted the attention of researchers, manufacturers, and insurance companies in the automotive industry. Different Deep Learning (DL) architectures ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2020.3017883

Bi-Objective Portfolio Optimization Under ESG Volatility via a MOPSO-Deep Learning Algorithm

Imma Lory Aprea, Gianni Bosi, Gabriele Sbaiz, Salvatore Scognamiglio • Mathematics (2025)

In this paper, we tackle a bi-objective optimization problem in which we aim to maximize the portfolio diversification and, at the same time, minimize the portfolio volatility, where the ESG (Environmental, Social, and Governance) informati...

DOAJ Open Access (DOAJ) DOI: 10.3390/math13203308

Gene expression inference with deep learning

Yifei Chen, Yi Li, Rajiv Narayan, Aravind Subramanian et al. • Bioinformatics (2016)

MOTIVATION: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dro...

OPENALEX Open Access DOI: https://doi.org/10.1093/bioinformatics/btw074 PMC: 4908320

Book Review: Deep Learning

Kwang Gi Kim • Healthcare Informatics Research (2016)

This book offers a solution to more intuitive problems in these areas. These solutions allow computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined in terms of its relation...

OPENALEX cc-by-nc DOI: https://doi.org/10.4258/hir.2016.22.4.351

Deep Learning in Medical Ultrasound Analysis: A Review

Shengfeng Liu, Yi Wang, Xin Yang, Baiying Lei et al. • Engineering (2019)

Ultrasound (US) has become one of the most commonly performed imaging modalities in clinical practice. It is a rapidly evolving technology with certain advantages and with unique challenges that include low imaging quality and high variabil...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eng.2018.11.020

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

A Selective Overview of Deep Learning

Jianqing Fan, Cong Ma, Yiqiao Zhong • Statistical Science (2021)

Deep learning has achieved tremendous success in recent years. In simple words, deep learning uses the composition of many nonlinear functions to model the complex dependency between input features and labels. While neural networks have a l...

OPENALEX Open Access DOI: https://doi.org/10.1214/20-sts783 PMC: 8300482

Deep Learning for Cardiac Image Segmentation: A Review

Chen Chen, Chen Qin, Huaqi Qiu, Giacomo Tarroni et al. • Frontiers in Cardiovascular Medicine (2020)

Deep learning has become the most widely used approach for cardiac image segmentation in recent years. In this paper, we provide a review of over 100 cardiac image segmentation papers using deep learning, which covers common imaging modalit...

OPENALEX cc-by DOI: https://doi.org/10.3389/fcvm.2020.00025 PMC: 7066212