AI sheds light on hard-to-study ocean currents

The Indonesian Throughflow carries both warm water and fresh water from the Pacific into the Indian Ocean. As the only ...

AMC Health Announces Breakthrough in AI-Driven Alert Precision for Virtual Care Program

New data science-driven alert framework expected to reduce clinician burden by 45% while preserving industry-leading ...
Security Boulevard

NDSS 2025 – A New PPML Paradigm For Quantized Models

Tianpei Lu (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Bingsheng Zhang (The State Key Laboratory of Blockchain and Data Security, Zhejiang University), Xiaoyuan ...
Beebom

AI vs Machine Learning: What is the Difference?

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Frontiers

Comparative study of machine learning and deep learning in predicting the shear strength of marine sand and polymer layer interfaces interface under marine temperature effects

In marine engineering, polymer layers are anti-seepage barrier materials. The mechanical interaction between marine sand and polymer layer significantly affects overall structural stability. In this ...
IEEE

Development of a Machine Learning-Based Model for an Intelligent Ambulance Detection System using CNN

Abstract: One of the major challenges faced by ambulances is heavy traffic. When caught in congestion, ambulances can be delayed for longer periods, which poses a significant risk to patients' lives.
Frontiers

MLVI-CNN: a hyperspectral stress detection framework using machine learning-optimized indices and deep learning for precision agriculture

Department of Electronics Communication Engineering, SRM Institute of Science and Technology, Vadapalani Campus, Chennai, India Introduction: Early and accurate detection of crop stress is vital for ...
Scientific Research Publishing

Abu-Nimeh, S., Nappa, D., Wang, X. and Nair, S. (2007) A Comparison of Machine Learning Techniques for Phishing Detection. Proceedings of the Anti-Phishing Working Groups 2nd ...

ABSTRACT: Phishing attacks remain a pervasive threat in the cybersecurity landscape, necessitating intelligent and scalable detection mechanisms. This paper suggests a deep learning-based method for ...
Scientific Research Publishing

Mahajan, R. and Siddavatam, I. (2018) Phishing Website Detection Using Machine Learning Algorithms. International Journal of Computer Applications, 181, 45-47.

ABSTRACT: Phishing attacks remain a pervasive threat in the cybersecurity landscape, necessitating intelligent and scalable detection mechanisms. This paper suggests a deep learning-based method for ...
IEEE

Hybrid Ensemble Learning Model Combining BERT and CNN for Predicting Urban Rail Transit Accident Consequences

Abstract: Urban Rail Transit (URT) accidents not only seriously affect the safety and reliability of its operations, but also reduce service level to passengers. Based on historical URT accident data, ...