Academic Articles & Research Papers

Deep Learning for Spatio-Temporal Data Mining: A Survey

With the fast development of various positioning techniques such as Global Position System (GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly available nowadays. Mining valuable knowledge from spatio-temp...

The unreasonable effectiveness of deep learning in artificial intelligence

Deep learning networks have been trained to recognize speech, caption photographs, and translate text between languages at high levels of performance. Although applications of deep learning networks to real-world problems have become ubiqui...

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

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 ...

A Survey on Deep Learning for Human Mobility

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...

Anemia Modelling Using the Multiple Regression Analysis

The aim of this article is to forecast anemia from a population through biomedical variables of individuals using the multiple linear regression model. The study is conducted in terms of dataset consisting of 539 subjects provided from bloo...

Siamese text classification network (SiamTCN) for multi-class multi-label information extraction of typhoon disasters from social media data

Accurately monitoring disaster effects is a crucial task in relief efforts (e.g. typhoon rescue). Social media data plays a vital role in disaster management, while deep learning-based methods gain more attention in typhoon disaster researc...

Deep Learning-Based Land Cover Extraction from Very-High-Resolution Satellite Imagery for Assisting Large-Scale Topographic Map Production

The demand for large-scale topographic maps in Indonesia has significantly increased due to the implementation of several government initiatives that necessitate the utilization of spatial data in development planning. Currently, the nation...

Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery

Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...

Deep Learning in Chemistry

Machine learning enables computers to address problems by learning from data. Deep learning is a type of machine learning that uses a hierarchical recombination of features to extract pertinent information and then learn the patterns repres...

Deep Learning

Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human c...

AutodiDAQt: Simple Scientific Data Acquisition Software with Analysis-in-the-Loop

Scientific data acquisition is a problem domain that has been underserved by its computational tools despite the need to efficiently use hardware, to guarantee validity of the recorded data, and to rapidly test ideas by configuring experime...

Disrupted cortex-wide dynamics impair motor planning in Shank3-mutant mice.

Interpretable machine learning to detect well integrity issues

The problem of timely and accurate evaluation of well integrity is becoming increasingly relevant in the context of mature field development, high wellstream water cut, and a growing number of old wells. For production casing diagnostics, g...

Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling

Xishu Gardens, an exemplary narrative of classical Chinese gardens, faces challenges in preserving its commemorative spatial structures while accommodating modern visitors’ needs. While trajectory analysis is critical, existing studies stru...

Machine learning-assisted three-dimensional mapping of the facial soft tissues in Saudi Arabian adults with skeletal class I relationship

OBJECTIVES: This study aimed to evaluate facial soft-tissue features in adults with skeletal Class I relationships using three-dimensional (3D) imaging and machine learning to identify sex-specific anthropometric patterns and provide refere...

Aerosol Optical Depth Retrieval from MODIS Using a Physically Informed Machine Learning Framework

Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...

Machine learning applications in epilepsy

Machine learning leverages statistical and computer science principles to develop algorithms capable of improving performance through interpretation of data rather than through explicit instructions. Alongside widespread use in image recogn...

Predicting Urban Quality of Life Using Machine Learning on Street Images and Personal Information with Statistical Feature Selection: A Comparative Study of Bangkok and London

This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...

Evaluation of the Applications of using Global free Digital Elevation Models and GNSS-RTK data for Agricultural purposes in Egypt using Machine Learning

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigat...