With the rapid development of precision agriculture, seed germination detection is crucial for crop monitoring and variety selection. Existing fully supervised detection methods rely on large-scale ...
Distinguished delegates, colleagues and friends, Writers and futurists have long echoed Alvin and Heidi Toffler’s idea that “the future arrives too fast…and in the wrong order.” Today, we know, the ...
├── src/ # Source code modules │ ├── lstm_model.py # LSTM implementation with PyTorch │ ├── forecasting_models.py # ARIMA, Prophet, and statistical models │ ├── anomaly_detection.py # Anomaly ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Non-Commercial (NC): Only non-commercial uses of the work are permitted. No ...
Over the past decade, financial fraud has emerged as a critical challenge in rural communities, where limited financial literacy, weak digital infrastructure, and social vulnerabilities make ...
Maritime Trajectory Anomaly Detection is extremely difficult for a vast number of reasons, the most prevelent of which is the lack of expert labeled ground truth data. Without a source of expert ...
ABSTRACT: Purpose: The purpose of this study is to develop a scalable, risk-aware artificial intelligence (AI) framework capable of detecting financial fraud in high-throughput digital transaction ...
Abstract: Log-based anomaly detection (LAD) is one of the dominant approaches to improving the reliability and security of software systems. Presently, despite the efficacy demonstrated by ...
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