Hey Redditors,<\/p>\n
I know the cars196<\/a> dataset is nothing new, but I wanted to share some label errors and outliers that I found within it.<\/p>\n It\u2019s interesting to note that the primary goal of the original paper<\/a> that curated\/used this dataset was \u201cfine-grained categorization\u201d meaning discerning the differences between something like a Chevrolet Cargo Van and a GMC Cargo Van. I found numerous examples of images that exhibit very nuanced<\/strong> mislabelling which is directly counterintuitive to the task they sought to research. <\/p>\n Here are a few examples of nuanced label errors that I found:<\/p>\n Audi TT RS Coupe labeled as an Audi TT Hatchback Audi S5 Convertible labeled as an Audi RS4 Jeep Grand Cherokee labeled as a Dodge Durango <\/p>\n I also found examples of outliers and generally ambiguous images:<\/p>\n multiple cars in one image top-down style images vehicles that didn’t belong to any classes. <\/p>\n I found these issues to be pretty interesting, yet I wasn’t surprised. It’s pretty well known that many common ML datasets exhibit thousands of errors<\/a>. <\/p>\n If you’re interested in how I found them, feel free to read about it here<\/a>.<\/p>\n<\/div>\n submitted by \/u\/cmauck10 <\/a>
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