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October 19, 2025Scientific Reports0 citationsOpen Access

Examining Recurrent Deep Neural Networks in Visual Recognition Performance

Recurrent issues with deep neural network models of visual recognition

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Authors

TMTimothée Maniquet HBHans Op de Beeck ACAndrea I. Costantino

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Overview

This analysis reveals recurrent deep neural networks do not consistently outperform feedforward models in visual recognition tasks, indicating complexity in model design.

Key Points

Increased model size significantly enhanced performance in visual recognition tasks, while architecture did not impact results.
Larger models showed better alignment with human perceptions of task difficulty, regardless of architecture used.
The study identified that recurrent models may not be superior to feedforward counterparts for modeling human behavior in recognition tasks.
Findings suggest reconsideration of recurrent deep neural networks as ideal representations of human visual recognition.

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Maniquet et al. (2025) studied this question.

synapsesocial.com/papers/68f500b442a2eee15b0a0e4d https://doi.org/10.1038/s41598-025-20245-w

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October 19, 2025Scientific Reports0 citationsOpen Access

Examining Recurrent Deep Neural Networks in Visual Recognition Performance

Recurrent issues with deep neural network models of visual recognition

View Full Paper

Authors

TMTimothée Maniquet HBHans Op de Beeck ACAndrea I. Costantino

Discussion

Member takes

Overview

This analysis reveals recurrent deep neural networks do not consistently outperform feedforward models in visual recognition tasks, indicating complexity in model design.

Key Points

Increased model size significantly enhanced performance in visual recognition tasks, while architecture did not impact results.
Larger models showed better alignment with human perceptions of task difficulty, regardless of architecture used.
The study identified that recurrent models may not be superior to feedforward counterparts for modeling human behavior in recognition tasks.
Findings suggest reconsideration of recurrent deep neural networks as ideal representations of human visual recognition.

Ask AI

Helpful

Bookmark

View Full Paper

Cite This Study

Maniquet et al. (2025) studied this question.

synapsesocial.com/papers/68f500b442a2eee15b0a0e4d https://doi.org/10.1038/s41598-025-20245-w

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