This approach suggests a quicker method for dataset creation using sparse, iteratively enhanced annotations. Future work will aim to implement further iterative ...
This study investigates the application of iterative sparse annotations for semantic segmentation in remote-sensing imagery, focusing on minimizing the ...
A DATA-CENTRIC APPROACH FOR RAPID GENERATION OF REMOTE SENSING DATASETS USING ITERATIVE LEARNING AND SPARSE ANNOTATIONS ; Session: WE2.R1: Deep Learning for ...
This approach suggests a quicker method for dataset creation using sparse, iteratively enhanced annotations. Future work will aim to ...
A Data-Centric Approach for Rapid Dataset Generation Using Iterative Learning and Sparse Annotations. Conference Paper. Jul 2023.
The presented method architecture is divided into three parts: (1) source code collection, which utilizes the top web service APIs from ProgrammableWeb ( ...
Missing: Rapid | Show results with:Rapid
Data-centric AI is an emerging approach for solving machine learning (ML) problems. It is a collection of various data manipulation techniques that allow ML ...
Missing: Rapid | Show results with:Rapid
Aug 8, 2023 · I work specifically in data quality (research) so I've been following the project for a while, but I'm curious whether you really make a case of ...
Active learning is an iterative labeling procedure that involves humans in the loop. In each iteration, the algorithm selects an unlabeled sample or batch of ...
May 26, 2024 · From a data-centric perspective, the performance of MLLMs heavily relies on the quality and diversity of the multimodal datasets used throughout ...