Abstract: This paper presents a novel deep learning framework for classifying Babylonian numerals by integrating Convolutional Neural Networks (CNNs) with a hybrid CNN-SVM model. The core ...
Abstract: Modeling of nonlinear loads is crucial for analyzing and evaluating power quality in modern power system. To further enhance both accuracy and robustness, a novel data-driven nonlinear load ...
Microsoft has announced that the Microsoft Agent Framework has reached Release Candidate status for both .NET and Python. This milestone indicates that the API surface is stable and feature-complete ...
Abstract: Accurate real-time fault detection, localization, and classification techniques are necessary to maintain grid stability and prevent faults. Traditional techniques have low accuracy rates, ...
A sprawling Chinese influence operation — accidentally revealed by a Chinese law enforcement official’s use of ChatGPT — focused on intimidating Chinese dissidents abroad, including by impersonating ...
Abstract: Verification of signatures is critical for authentication procedures in the legal, banking, and financial domains. A cutting-edge, AI-powered technology called SigVerify Project uses deep ...
This repository is the code implementation of the paper AgriFM: A Multi-source Temporal Remote Sensing Foundation Model for Agriculture Mapping. AgriFM is a multi-source temporal remote sensing ...
What are meteorologists supposed to do when the models they rely on disagree so sharply? And how should you interpret the forecast?
Kronos is the first open-source foundation model for financial candlesticks (K-lines), trained on data from over 45 global exchanges. Kronos is a family of decoder-only foundation models, pre-trained ...
Abstract: Oil and gas distribution through undersea pipelines requires continuous monitoring, especially when transmitting these resources through undersea pipelines, as operational failures can lead ...
Abstract: Olfactory perception prediction plays a vital role in multi-modal sensory research, offering insights for health monitoring and personalized experiences. In this work, we propose a novel CNN ...
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 ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results