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Correction

Correction: Jung et al. GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements. Mathematics 2025, 13, 1867

1
Computer Science and Engineering, Konkuk University, Seoul 05029, Republic of Korea
2
Department of Software, Korea Aerospace University, Goyang 10540, Republic of Korea
3
Department of Otolaryngology-Head & Neck Surgery, College of Medicine, Konkuk University, Seoul 05030, Republic of Korea
*
Authors to whom correspondence should be addressed.
Mathematics 2025, 13(17), 2753; https://doi.org/10.3390/math13172753
Submission received: 8 August 2025 / Accepted: 10 August 2025 / Published: 27 August 2025

Error in Table

In the original publication [1], there was a mistake in Table 1 as published. After publication, we discovered an error in Table 1, specifically in the Output Sizes column. This table is essential for understanding the architecture of our dual-pathway CNN, and the incorrect output channel numbers for both the main pathway and sub-pathway may lead to confusion or prevent the reproducibility of our model. The corrected Table 1 appears below.

Missing Funding

In the original publication, the funder “This work was supported by the Institute of Information & communications Technology Planning & Evaluation (IITP) under the metaverse support program to nurture the best talents under Grant IITP-2025-RS-2023-00256615 funded by the Korea government (MSIT).” was not included.
The authors state that the scientific conclusions are unaffected. This correction was approved by the Academic Editor. The original publication has also been updated.

Reference

  1. Jung, H.; Ham, S.; Kil, H.; Shin, J.E.; Kim, E.Y. GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements. Mathematics 2025, 13, 1867. [Google Scholar] [CrossRef]
Table 1. The architecture details of the dual-pathway CNN. The orange colors mark fewer channels for the sub-pathway. The backbone is ResNet50.
Table 1. The architecture details of the dual-pathway CNN. The orange colors mark fewer channels for the sub-pathway. The backbone is ResNet50.
StageMain PathwaySub-PathwayOutput Sizes 1
Input--Main: 3 × 44 2
Sub: 3 × 44 2
conv1 7 2 ,   64
Stride   2 2
7 2 ,   8
Stride   2 2
Main: 64 × 22 2
Sub: 8 × 22 2
conv2_x 1 2 ,   64 3 2 ,   64 1 2 ,   256 × 3 1 2 ,   8 3 2 ,   8 1 2 ,   32 × 3 Main: 256 × 22 2
Sub: 32 × 22 2
conv3_x 1 2 ,   128 3 2 ,   128 1 2 ,   512 × 4 1 2 ,   16 3 2 ,   16 1 2 ,   64 × 4 Main: 512 × 11 2
Sub: 64 × 11 2
conv4_x 1 2 ,   256 3 2 ,   256 1 2 ,   1024 × 6 1 2 ,   32 3 2 ,   32 1 2 ,   128 × 6 Main: 1024 × 6 2
Sub: 128 × 6 2
conv5_x 1 2 ,   512 3 2 ,   512 1 2 ,   2048 × 3 1 2 ,   64 3 2 ,   64 1 2 ,   256 × 3 Main: 2048 × 3 2
Sub: 256 × 3 2
global average pooling, metadata concatenate, fc layer2 (HC, AD)
1 Output sizes: channel × height × width.
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Share and Cite

MDPI and ACS Style

Jung, H.; Ham, S.; Kil, H.; Shin, J.E.; Kim, E.Y. Correction: Jung et al. GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements. Mathematics 2025, 13, 1867. Mathematics 2025, 13, 2753. https://doi.org/10.3390/math13172753

AMA Style

Jung H, Ham S, Kil H, Shin JE, Kim EY. Correction: Jung et al. GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements. Mathematics 2025, 13, 1867. Mathematics. 2025; 13(17):2753. https://doi.org/10.3390/math13172753

Chicago/Turabian Style

Jung, Hyuntaek, Shinwoo Ham, Hyunyoung Kil, Jung Eun Shin, and Eun Yi Kim. 2025. "Correction: Jung et al. GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements. Mathematics 2025, 13, 1867" Mathematics 13, no. 17: 2753. https://doi.org/10.3390/math13172753

APA Style

Jung, H., Ham, S., Kil, H., Shin, J. E., & Kim, E. Y. (2025). Correction: Jung et al. GazeMap: Dual-Pathway CNN Approach for Diagnosing Alzheimer’s Disease from Gaze and Head Movements. Mathematics 2025, 13, 1867. Mathematics, 13(17), 2753. https://doi.org/10.3390/math13172753

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