In the literature of deep saliency models, a loss function or a combination of several ones is chosen based on intuition, expertise of the authors or sometimes mathematical formulation of a model.
Sep 17, 2021
Jul 4, 2019 · Numerous models in the literature present new ways to design neural networks, to arrange gaze pattern data, or to extract as much high and low- ...
Aug 7, 2019 · For this purpose, we first categorize loss functions per type of metric : (i) pixel-based comparisons e.g. Mean Square. Error, Absolute Errors ...
In this work, we explore some of the most popular loss functions that are used in deep saliency models. We demonstrate that on a fixed network architecture, ...
People also ask
What is the loss function in deep learning?
What is the loss function for deep Q network?
What is the loss function of T5 model?
What is the loss function in MSE?
They find that a loss consisting of a linear combination of several terms, individually focusing on a different aspect, with for instance a pixel-based term, a ...
However, one key part of a typical deep learning model is often neglected: the choice of the loss function. In this work, we explore some of the most popular ...
Jun 12, 2020 · Which loss function should you use to train your saliency model? This is this question we have investigated in the following paper: Bruckert ...
Deep Saliency Models : The Quest For The Loss Function ... We demonstrate that on a fixed network architecture, modifying the loss function can significantly ...
Deep Saliency Models : The Quest For The Loss Function. - DBLP
dblp.org › rec › corr › abs-1907-02336
Jul 8, 2019 · Bibliographic details on Deep Saliency Models : The Quest For The Loss Function.
Jul 4, 2019 · DEEP SALIENCY MODELS : THE QUEST FOR THE LOSS FUNCTION. Alexandre Bruckert1, Hamed R. Tavakoli2, Zhi Liu3, Marc Christie1, Olivier Le Meur1. 1 ...