# Hyperparameter Analysis for Image Captioning

arXiv: https://arxiv.org/abs/2006.10923 · HTML: https://mlsanity.com/paper/2006.10923/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Jun 2020.

## Built on by (most cited first, 1 of 1)

- [An Ensemble Model with Attention Based Mechanism for Image Captioning](https://mlsanity.com/paper/2501.14828/) (2025)

## Abstract (arXiv)

In this paper, we perform a thorough sensitivity analysis on state-of-the-art image captioning approaches using two different architectures: CNN+LSTM and CNN+Transformer. Experiments were carried out using the Flickr8k dataset. The biggest takeaway from the experiments is that fine-tuning the CNN encoder outperforms the baseline and all other experiments carried out for both architectures.