Academic Articles & Research Papers

An Explainable Multi-Modal Deep Learning Framework for Investigating the Influences of Dynamic Environmental Exposure on Momentary Stress.

Deep learning-based segmentation, grading and genotype classification of glioma: a literature analysis.

Construction of musculoskeletal quantitative model based on deep learning and study of musculoskeletal relationship in patients with osteoporosis.

Unequal economic impacts of climate change via idealized carbon dioxide removal: Insights from deep learning.

Artificial intelligence, explainable deep learning, and generative models for osteoporosis and bone disease prediction: a systematic review and future research roadmap.

Machine Learning, Deep Learning, and IoT for Waste Classification and Intelligent Waste Management: A PRISMA-Based Systematic Review.

LncRNA-Top: Controlled deep learning approaches for lncRNA gene regulatory relationship annotations across different platforms

Summary: By soaking microRNAs (miRNAs), long non-coding RNAs (lncRNAs) have the potential to regulate gene expression. Few methods have been created based on this mechanism to anticipate the lncRNA-gene relationship prediction. Hence, we pr...

Automated wound care by employing a reliable U-Net architecture combined with ResNet feature encoders for monitoring chronic wounds

Quality of life is greatly affected by chronic wounds. It requires more intensive care than acute wounds. Schedule follow-up appointments with their doctor to track healing. Good wound treatment promotes healing and fewer problems. Wound ca...

Automatic Detection of Abnormal EEG Signals Using WaveNet and LSTM

Neurological disorders have an extreme impact on global health, affecting an estimated one billion individuals worldwide. According to the World Health Organization (WHO), these neurological disorders contribute to approximately six million...

A deep learning recognition model for landslide terrain based on multi-source data fusion

The traditional high-level remote landslide recognition efficiency which relies on the artificial discrimination of geological experts is low. In this paper, an automatic landslide terrain recognition model based on deep learning is develop...

Non-Motorized License Plate Recognition and Localization Method Based on Semantic Alignment and Hierarchical Optimization

Holding non-motorized vehicles accountable for legal violations effectively enhances urban traffic safety. Non-motorized vehicle license plates are characterized by small size, dense distribution, and ease of being obscured, which leads to ...

Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images

Retinal optical coherence tomography (OCT) imaging is a valuable tool for assessing the condition of the back part of the eye. The condition has a great effect on the specificity of diagnosis, the monitoring of many physiological and pathol...

A Systematic Review of Deep Learning Approaches for Information Disorder Detection on Social Media: The Context of Misinformation, Disinformation, and Mal-information

Social media platforms have become powerful tools for communication, information exchange, networking, and community building. However, their widespread use has facilitated the proliferation of misinformation, disinformation, and mal-inform...

Spatial layout optimization model integrating layered attention mechanism in the development of smart tourism management

Tourism demand projection is paramount for both corporate operations and destination management, facilitating tourists in crafting bespoke, multifaceted itineraries and enriching their vacation experiences. This study proposes a multi-layer...

Transportation Engineering

Abstract Transportation engineering is a multidisciplinary subject within civil engineering involving the planning, design, operation, and maintenance of transportation systems and associated infrastructure such as highways, roads, and rail...

Searching for galaxy cluster-scale strong lenses from the DESI legacy imaging surveys

IntroductionGalaxy cluster-scale strong gravitational lensing systems are rare yet valuable tools for investigating dark matter and dark energy, as well as providing the opportunity to study the distant universe at flux levels and spatial r...

Algae-Mamba: A Spatially Variable Mamba for Algae Extraction From Remote Sensing Images

To maintain marine ecosystem health, effective algae monitoring is essential. Traditional threshold-based methods and standard machine learning techniques often fall short in accurately and automatically distinguishing algae types. This stu...

ProtoMix: Unified Prototype Learning for Semantic Change Detection in Remote Sensing

As an emerging topic, semantic change detection (SCD) in remote sensing aims to both identify the locations of changes before and after events and determine the land cover (LC) classes of changed regions. While deep learning has demonstrate...

IceRegionShip: Optical Remote Sensing Dataset for Ship Detection in Ice-Infested Waters

As shipping routes and resource exploration move toward high-latitude oceans, sea ice becomes a major threat to the safety of ship navigation, posing significant challenges to the shipping industry and offshore resource development. Continu...

Evaluating Uses of Deep Learning Methods for Causal Inference

Logistic regression (LR) is a popular method that is used for estimating causal effects in observational studies using propensity scores. We examine the use of deep learning models such as the deep neural network (DNN), PropensityNet (PN), ...