This study proposes a novel hybrid deep learning framework that integrates a Large Language Model (LLM) with a Transformer architecture for stock price forecasting. The research addresses a critical theoretical gap in existing approaches that empirically combine textual and numerical data without a formal understanding of their interaction mechanisms. We conceptualize a prompt-based LLM as a mathematically defined signal generator, capable of extracting directional market sentiment and an associated confidence score from financial news. These signals are then dynamically fused with structured historical price features through a noise-robust gating mechanism, enabling the Transformer to adapt... More >

Gaze estimation plays a vital role in human-computer interaction, driver monitoring, and psychological analysis. While state-of-the-art appearance-based methods achieve high accuracy using deep learning, they often demand substantial computational resources, including GPU acceleration and extensive training, limiting their use in resource-constrained or real-time scenarios. This paper introduces GeoGaze, a novel, lightweight, training-free framework that infers categorical gaze direction (“Left”, “Center”, “Right”) solely from geometric analysis of facial landmarks. Leveraging the high-precision 478-point face mesh and iris landmarks provided by MediaPipe, GeoGaze computes a simp... More >

Studies have established that an ideal environment is critical for maximizing a student's learning potential. For educators, monitoring student behavior, engagement, and psychological state is essential for ensuring effective instruction. This paper introduces an automated learning analytics system designed to assist teachers by analyzing these parameters and providing actionable feedback. The system utilizes multiple cameras in conjunction with deep learning and computer vision to record and analyze classroom sessions, assessing student movement, gestures, and posture to generate summary reports. The framework integrates several high-performance models to achieve this. For facial recognitio... More >