Aug 14, 2022 · Task 1: multi-class classification on the modified CIFAR10 dataset (airplane, automobile, bird, cat, dog, frog, ship and truck labels, modifications explained below). Task 2: …

Learn the basics of multi-task learning in deep neural networks. See its practical applications, when to use it, & how to optimize the multi-task learning process.

Jan 19, 2023 · Multi-Task Learning (MTL) is a type of machine learning technique where a model is trained to perform multiple tasks simultaneously. In deep learning, MTL refers to training a …

Jul 12, 2021 · Some of the uses cases that this can solve in the computer vision domain are: Prediction of prices and type of house; Gender and age detection from faces; Crop …

Mar 28, 2022 · Multi-task learning (MTL) aims to leverage useful information across tasks to improve the generalization capability of a model. This thesis is concerned with multi-task …

Jun 29, 2020 · Multi-task training requires loss aggregation. There are three main strategies: Scale loss to about the same range and train the whole network with uniform loss weights.

May 17, 2021 · Multitask learning is actually inspired by human learning. When learning new tasks, don’t you tend to apply the knowledge gained when learning related tasks. For instance, …

Mar 20, 2023 · In computer vision, MTL has shown great potential in addressing challenges such as image segmentation, key-point detection, and edge detection. It has demonstrated …

In this thesis, we will present some state-of-the-art models to solve image classification and object detection problems. We will define multi-task learning, how we can train multi-task models, …

Multi-task learning has been shown to improve the performance of computer vision models by leveraging shared knowledge between tasks. Another important aspect of computer vision is …