Finding Misdetections in Unlabeled Image Database: Toward Reliable ...
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In this paper, we propose a framework of partial image retrieval to analyze and debug a target detection model.
These similar images provide us with insights into the misdetection by object detection models, which will be useful in resolving the issue. We qualitatively ...
Given an image with incorrectly detected objects, our method discovers similar images that also contain incorrectly detected objects from a large unlabeled ...
Computer-aided foliage image retrieval systems have the potential to dramatically speed up the process of plant species identification. Despite previous ...
Naoki Mitsumoto's 3 research works with 30 citations, including: Finding Misdetections in Unlabeled Image Database: Toward Reliable Object Detection.
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Mar 17, 2019 · Without negative data a network may learn too abstract features. Then the network may find those features in other objects it should not detect.
Missing: Misdetections | Show results with:Misdetections
Sep 4, 2023 · Unlock Insights from Unlabelled Images in Machine Learning: Exploring Object Detection Datasets with and without Labels.
Missing: Misdetections | Show results with:Misdetections
May 22, 2023 · Marking these images as null is the correct thing to do. Object detection models will learn not to predict unlabeled areas (background area) through their loss ...
Missing: Misdetections | Show results with:Misdetections
These networks combine efficiently sensor specific properties by using both early fusion and middle fusion for detecting road objects and their 2D localization.
Duration: 4:35:26
Posted: Jul 10, 2023
Posted: Jul 10, 2023
Missing: Misdetections Unlabeled Reliable