Academic Articles & Research Papers

Deep Learning for Geophysics: Current and Future Trends

Abstract Recently deep learning (DL), as a new data‐driven technique compared to conventional approaches, has attracted increasing attention in geophysical community, resulting in many opportunities and challenges. DL was proven to have the...

A review on deep learning in UAV remote sensing

Deep Neural Networks (DNNs) learn representation from data with an impressive capability, and brought important breakthroughs for processing images, time-series, natural language, audio, video, and many others. In the remote sensing field, ...

Deep learning for procedural content generation

Radiomics and deep learning in lung cancer

Deep learning in omics: a survey and guideline

Omics, such as genomics, transcriptome and proteomics, has been affected by the era of big data. A huge amount of high dimensional and complex structured data has made it no longer applicable for conventional machine learning algorithms. Fo...

Automated Website Fingerprinting through Deep Learning

Several studies have shown that the network traffic that is generated by a visit to a website over Tor reveals information specific to the website through the timing and sizes of network packets.By capturing traffic traces between users and...

Deep Learning via Semi-supervised Embedding

Hierarchical Multimodal Sleep Staging with Optimized EEG, EOG, and PPG Features for Wearable Applications

Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...

Controllable diffusion framework for imbalanced Phi OTDR events classification

Abstract The application of the $$\Phi$$ -OTDR (Phase-Optical Time Domain Reflectometry) system in real-time monitoring of power grid infrastructure has been proven effective in identifying and classifying various anomalies, such as digging...

An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders

Abstract Background Niacin Skin-Flushing Response (NSR) has emerged as a promising objective biomarker for the precise diagnosis of mental disorders. However, its diagnostic potential has been constrained by the limitations of traditional s...

Quantum Leap in Healthcare: A Comparative Analysis of AI/ML and Quantum Computing for Healthcare opportunities of the new era

The healthcare sector is undergoing rapid transformation driven by advances in artificial intelligence and machine learning, with quantum computing emerging as the next major breakthrough. This paper presents a comparative analysis of class...

Deep-learning–based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy

Abstract Background Non-contrast CT (NCCT) is first-line imaging for suspected acute ischemic stroke (AIS) but has limited early sensitivity; deep learning (DL) may improve patient-level detection. Objectives To estimate the diagnostic accu...

AI-Driven Optimization of Functional Feature Placement in Automotive CAD

The automotive industry increasingly relies on 3D modeling technologies to design and manufacture vehicle components with high precision. One critical challenge is optimizing the placement of latches that secure the dashboard side paneling,...

Evaluating the Accuracy of Deep Learning Models and Dental Postgraduate Students in Measuring Working Length on Intraoral Periapical X-rays: An In vitro Study

Background: The integration of artificial intelligence in dentistry has seen remarkable advancements, especially in diagnostic imaging. This study evaluates and compares the accuracy of deep learning models with that of dental postgraduate ...

Gene–gene interaction detection with deep learning

An open-source framework combines deep learning and permutations of gene interaction neural networks to detect complex gene–gene interactions and their significance in contributions to phenotypes....

An optimized deep learning framework for temporally stable real-time face detection in unconstrained video streams

Abstract Face detection in real-time video streams remains challenging because of dynamic variations in illumination, pose, motion blur, and partial occlusion. This paper proposes an optimized deep learning framework that integrates YOLOv12...

Ethical and legal concerns in artificial intelligence applications for the diagnosis and treatment of lung cancer: a scoping review

IntroductionArtificial intelligence (AI) is increasingly integrating into the healthcare field, particularly in lung cancer care, including screening, diagnosis, treatment, and prognosis. While these applications offer promising advancement...

Deep learning in medical image registration: a review

This paper presents a review of deep learning (DL)-based medical image registration methods. We summarized the latest developments and applications of DL-based registration methods in the medical field. These methods were classified into se...

A Deep Learning Approach for Network Intrusion Detection System

A Network Intrusion Detection System (NIDS) helps system administrators to detect network security breaches in their organizations. However, many challenges arise while developing a flexible and efficient NIDS for unforeseen and unpredictab...

Machine learning in construction: From shallow to deep learning

The development of artificial intelligence technology is currently bringing about new opportunities in construction. Machine learning is a major area of interest within the field of artificial intelligence, playing a pivotal role in the pro...