: If your model has a limited context window, remove redundant frames using similarity thresholds to focus on meaningful motion. Normalization : Resize frames to a standard dimension (e.g., ) and normalize pixel values to a 2. Select a Model Architecture

: Useful if the task involves long-term dependencies, though largely superseded by Transformers in modern deep learning. 3. Implementation and Training

) at the Technion, where likely refers to the fourth programming assignment or a specific project task involving video data or sequence models.

: Effective for capturing spatial and temporal features simultaneously.

In a deep learning context, an MP4 is a sequence of frames. Your pipeline should handle extraction and normalization:

If your "piece" is intended for an educational setting like D2L (Brightspace), which is frequently used for such courses: