# Effect of Kernel Size on CNN-Vision-Transformer-Based Gaze Prediction Using Electroencephalography Data

arXiv: https://arxiv.org/abs/2408.03478 · HTML: https://mlsanity.com/paper/2408.03478/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 19 of its 48 references that are in the map.
- First posted on arXiv 6 Aug 2024.

## Builds on (most cited first, 19 of 19)

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- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://mlsanity.com/paper/1502.03167/) (2015)
- [Transformers in Vision: A Survey](https://mlsanity.com/paper/2101.01169/) (2021)
- [EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer Interfaces](https://mlsanity.com/paper/1611.08024/) (2016)
- [ImageNet-21K Pretraining for the Masses](https://mlsanity.com/paper/2104.10972/) (2021)
- [Deep learning-based electroencephalography analysis: a systematic review](https://mlsanity.com/paper/1901.05498/) (2019)
- [Machine Learning for Synthetic Data Generation: A Review](https://mlsanity.com/paper/2302.04062/) (2023)
- [EEGEyeNet: a Simultaneous Electroencephalography and Eye-tracking Dataset and Benchmark for Eye Movement Prediction](https://mlsanity.com/paper/2111.05100/) (2021)
- [Transfer Learning for Human Activity Recognition using Representational Analysis of Neural Networks](https://mlsanity.com/paper/2012.04479/) (2020)
- [Successfully Applying Lottery Ticket Hypothesis to Diffusion Model](https://mlsanity.com/paper/2310.18823/) (2023)
- [A Deep Learning Approach for the Segmentation of Electroencephalography Data in Eye Tracking Applications](https://mlsanity.com/paper/2206.08672/) (2022)
- [Time Majority Voting, a PC-based EEG Classifier for Non-expert Users](https://mlsanity.com/paper/2207.12662/) (2022)
- [Trends in Machine Learning and Electroencephalogram (EEG): A Review for Undergraduate Researchers](https://mlsanity.com/paper/2307.02819/) (2023)
- [ViT2EEG: Leveraging Hybrid Pretrained Vision Transformers for EEG Data](https://mlsanity.com/paper/2308.00454/) (2023)
- [BrainActivity1: A Framework of EEG Data Collection and Machine Learning Analysis for College Students](https://mlsanity.com/paper/2207.13239/) (2022)
- [Vector-Based Data Improves Left-Right Eye-Tracking Classifier Performance After a Covariate Distributional Shift](https://mlsanity.com/paper/2208.00465/) (2022)
- [Too Fine or Too Coarse? The Goldilocks Composition of Data Complexity for Robust Left-Right Eye-Tracking Classifiers](https://mlsanity.com/paper/2209.03761/) (2022)

## Abstract (arXiv)

In this paper, we present an algorithm of gaze prediction from Electroencephalography (EEG) data. EEG-based gaze prediction is a new research topic that can serve as an alternative to traditional video-based eye-tracking. Compared to the existing state-of-the-art (SOTA) method, we improved the root mean-squared-error of EEG-based gaze prediction to 53.06 millimeters, while reducing the training time to less than 33% of its original duration. Our source code can be found at https://github.com/AmCh-Q/CSCI6907Project