Select Language

AI社区

公开数据集

加州理工学院 256 无重命名 2

加州理工学院 256 无重命名 2

1105.66M
440 浏览
0 喜欢
0 次下载
0 条讨论
Earth and Nature,Universities and Colleges,Image Data Classification

数据结构 ? 1105.66M

    Data Structure ?

    * 以上分析是由系统提取分析形成的结果,具体实际数据为准。

    README.md

    Context (This dataset does not contain the RENAME2 File to avoid errors) The Caltech 256 is considered an improvement to its predecessor, the Caltech 101 dataset, with new features such as larger category sizes, new and larger clutter categories, and overall increased difficulty. This is a great dataset to train models for visual recognition: How can we recognize frogs, cell phones, sail boats and many other categories in cluttered pictures? How can we learn these categories in the first place? Can we endow machines with the same ability? Content There are 30,607 images in this dataset spanning 257 object categories. Object categories are extremely diverse, ranging from grasshopper to tuning fork. The distribution of images per category are: Min: 80 Med: 100 Mean: 119 Max: 827 Acknowledgements Original data source and banner image: http://www.vision.caltech.edu/Image_Datasets/Caltech256/ When using this dataset, please remember to cite: Griffin, G. Holub, AD. Perona, P. The Caltech 256. Caltech Technical Report. Inspiration Can you build a model that IDs certain images? What is the object? Is it a backpack, chopsticks, fried egg, or one of the other 253 object categories?
    ×

    帕依提提提温馨提示

    该数据集正在整理中,为您准备了其他渠道,请您使用

    注:部分数据正在处理中,未能直接提供下载,还请大家理解和支持。
    暂无相关内容。
    暂无相关内容。
    • 分享你的想法
    去分享你的想法~~

    全部内容

      欢迎交流分享
      开始分享您的观点和意见,和大家一起交流分享.
    所需积分:0 去赚积分?
    • 440浏览
    • 0下载
    • 0点赞
    • 收藏
    • 分享