About This repository demonstrates a simple end-to-end approach for predicting historical stock closing prices using recurrent neural networks (RNNs), specifically Long Short-Term Memory (LSTM) ...

Accurately obtaining the total nitrogen and nicotine content of tobacco plants and their vertical distribution within the canopy is crucial for smart management and quality assessment. However, the ...

Ritwik is a passionate gamer who has a soft spot for JRPGs. He's been writing about all things gaming for six years and counting. No matter how great a title's gameplay may be, there's always the ...

Deep learning-based image steganalysis has progressed in recent times, with efforts more concerted toward prioritizing detection accuracy over lightweight frameworks. In the context of AI-driven ...

ABSTRACT: SQL injection attacks pose a critical threat to web application security, exploiting vulnerabilities to gain access, or modify sensitive data. Traditional rule-based and machine learning ...

Abstract: Recurrent Neural Network (RNN) and its variants, such as Long Short-Term Memory (LSTM), have achieved remarkable success in sequential data processing tasks. The representations learned by ...

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...

Abstract: A Recurrent Neural Network (RNN) with a Long Short Term Memory (LSTM) implementation can be effectively utilized to classiiy the radar signature of zero to three human gaits, based on their ...