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Deep learning for power quality

Roger Alves de Oliveira, Math Bollen • Electric Power Systems Research (2022)

This paper aims to introduce deep learning to the power quality community by reviewing the latest applications and discussing the open challenges of this technology. Publications covering deep learning to power quality are stratified in ter...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.epsr.2022.108887

Deep learning for electroencephalogram (EEG) classification tasks: a review

Alexander Craik, Yongtian He, Jose Luis Contreras-Vidal • Journal of Neural Engineering (2019)

OBJECTIVE: Electroencephalography (EEG) analysis has been an important tool in neuroscience with applications in neuroscience, neural engineering (e.g. Brain-computer interfaces, BCI's), and even commercial applications. Many of the analyti...

OPENALEX cc-by DOI: https://doi.org/10.1088/1741-2552/ab0ab5

Deep learning approaches to biomedical image segmentation

Intisar Rizwan I Haque, Jeremiah J. Neubert • Informatics in Medicine Unlocked (2020)

The review covers automatic segmentation of images by means of deep learning approaches in the area of medical imaging. Current developments in machine learning, particularly related to deep learning, are proving instrumental in identificat...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.imu.2020.100297

Deep learning: a statistical viewpoint

Peter L. Bartlett, Andrea Montanari A, Alexander Rakhlin • Acta Numerica (2021)

The remarkable practical success of deep learning has revealed some major surprises from a theoretical perspective. In particular, simple gradient methods easily find near-optimal solutions to non-convex optimization problems, and despite g...

OPENALEX cc-by DOI: https://doi.org/10.1017/s0962492921000027

Systemic Review and Meta-Analysis: The Application of AI-Powered Drone Technology with Computer Vision and Deep Learning Networks in Waste Management

Tyrone Bright, Sarp Adali, Cristina Trois • Drones (2025)

As the generation of Municipal Solid Waste (MSW) has exponentially increased, this poses a challenge for waste managers, such as municipalities, to effectively control waste streams. If waste streams are not managed correctly, they negative...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones9080550

An AI-Based Deep Learning with K-Mean Approach for Enhancing Altitude Estimation Accuracy in Unmanned Aerial Vehicles

Prot Piyakawanich, Pattarapong Phasukkit • Drones (2024)

In the rapidly evolving domain of Unmanned Aerial Vehicles (UAVs), precise altitude estimation remains a significant challenge, particularly for lightweight UAVs. This research presents an innovative approach to enhance altitude estimation ...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones8120718

Distributed biconnectivity-preserving flocking with fast obstacle avoidance for UAV swarms

Jiaxin Li, Tong Duan, Peng Yi, Zhen Zhang et al. • Complex & Intelligent Systems (2026)

Abstract Obstacles in low-altitude environments force unmanned aerial vehicle (UAV) swarms to frequently alter their flight paths and communication links, which can easily cause network interruptions. It remains a significant challenge for ...

DOAJ Open Access (DOAJ) DOI: 10.1007/s40747-026-02343-y

Deep learning as a tool for ecology and evolution

Marek L. Borowiec, Rebecca B. Dikow, Paul B. Frandsen, Alexander J. McKeeken et al. • Methods in Ecology and Evolution (2022)

Abstract Deep learning is driving recent advances behind many everyday technologies, including speech and image recognition, natural language processing and autonomous driving. It is also gaining popularity in biology, where it has been use...

OPENALEX cc-by-nc DOI: https://doi.org/10.1111/2041-210x.13901

An overview of deep learning in the field of dentistry

Jae Joon Hwang, Yun‐Hoa Jung, Bong‐Hae Cho, Min-Suk Heo • Imaging Science in Dentistry (2019)

PURPOSE: Artificial intelligence (AI), represented by deep learning, can be used for real-life problems and is applied across all sectors of society including medical and dental field. The purpose of this study is to review articles about d...

OPENALEX cc-by-nc DOI: https://doi.org/10.5624/isd.2019.49.1.1 PMC: 6444007

Privacy-Preserving Deep Learning

Reza Shokri, Vitaly Shmatikov • ACM SIGSAC Conference on Computer and Communications Security (CCS) (2015)

Deep learning based on artificial neural networks is a very popular approach to modeling, classifying, and recognizing complex data such as images, speech, and text. The unprecedented accuracy of deep learning methods has turned them into t...

OPENALEX DOI: https://doi.org/10.1145/2810103.2813687

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

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 longitudinal study on students’ self-regulated listening during transition to an English-medium transnational university in China

Sihan Zhou, Gene Thompson • Studies in Second Language Learning and Teaching (2023)

Listening to academic content in English medium instruction (EMI) classrooms at university can be a demanding task for students who transition from first language (L1) instructed secondary schools. This longitudinal mixed methods study anal...

DOAJ Open Access (DOAJ) DOI: 10.14746/ssllt.38281

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

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