Scientist turns people’s mental images into text using ‘mind-captioning’ technology

A scientist in Japan has developed a technique that uses brain scans and artificial intelligence to turn a person’s mental images into descriptive sentences.
Scientific Research Publishing

Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience ()

Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .

AI coding transforms data engineering: How dltHub's open-source Python library helps developers create data pipelines for AI in minutes

A quiet revolution is reshaping enterprise data engineering. Python developers are building production data pipelines in ...
IEEE

Research on Driver Trust Prediction based on the Attention-CNN Model

Driver trust in Automated Driving Systems (ADS) is a key factor for ensuring human-vehicle-cooperative driving safety. This study focuses on this aspect and conducts driving simulation experiments on ...
How-To Geek on MSN

How to run R-style linear regressions in Python the easy way

The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate correlation coefficient. If you look at the multiple regression we did, ...
IEEE

Comparison of MFCC and Spectrogram Analysis in Improving the Accuracy of CNN Models for Song Clip Prediction

Abstract: The performance of automatic music recognition models largely depends on the chosen feature extraction method. This study compares two widely used techniquesMFCC and Spectrograms-to ...
IEEE

Strategic and Sustainable ERP Decision Framework: Integrating Multi-Criteria Analysis with Deep-A-CNN-LSTM Models in Corporate Strategy

Abstract: Customizing enterprise resource planning (ERP) software to meet a company's unique operational requirements is a crucial consideration throughout implementation. It offers a framework in ...
IEEE

A Comparative Analysis of CNN-based Deep Learning Models for Landslide Detection

Abstract: Landslides inflict substantial societal and economic damage, underscoring their global significance as recurrent and destructive natural disasters. Recent landslides in northern parts of ...
IEEE

Advancing Predictive Maintenance in Smart Grids with Machine Learning Techniques Through Comparative Analysis of SVM and CNN Models

Abstract: Applying ML techniques into smart grid architectures has transformed the predictive maintenance to a level that can predict equipment failures before they occur. This approach reduces the ...
IEEE

A Hybrid CNN-ViT and GAN (HCVGAN) Model for Cocoa Leaf Disease Prediction

Abstract: Plant diseases pose a significant risk to farmers and impact crop yield and food safety. Early detection is crucial. In the proposed method, Vision Transformers (ViTs) and Convolutional ...
IEEE

Study of a Hybrid CNN-SVM Model for Stress Detection with Automated Heart Rate Variability Feature Extraction Method

Abstract: In the era of big data, stress detection techniques based on electrocardiogram (ECG) data play a crucial role in monitoring mental health and preventing mental disorders. Given that the ...
IEEE

DermNet-CNN: A Hyperparameter-Tuned CNN Model for Accurate Skin Disease Detection

Abstract: The diagnosis of skin disease is a critical area in healthcare, requiring high accuracy and reliability to ensure effective treatment. Traditional diagnostic methods often struggle with the ...