Pool.mp4 -

Propose a 3D Convolutional Neural Network (3D CNN) to extract spatial-temporal features. 4. Training & Evaluation

Explain how the video is converted into a 3D dataset (height, width, time). pool.mp4

Propose a 3D CNN model to estimate heat flux using pool.mp4 . 2. Related Work Propose a 3D Convolutional Neural Network (3D CNN)

Here is a structure for a solid academic/technical paper based on this theme: Propose a 3D CNN model to estimate heat flux using pool

Based on the prompt "pool.mp4" and the request to "put together a solid paper," the search results suggest a strong connection to , according to a recent Feb 2026 study. The video likely demonstrates the 3D modelling of bubble dynamics or the experimental setup described in that paper.

Explain saturated pool boiling on vertical tubes.

Describe the I3D (Inflated 3D) training on the dataset. Results: Present the accuracy of heat flux estimation. Discussion: Analyze how the model performs on the video. 5. Conclusion