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Our datasets and models
- > Specifications for dataset design, collection and annotation (PDF)
- > Datasets and models of EV batteries for deep learning objects detection algorithms and positioning tasks.
- > The EV batteries image dataset (Part 1) includes 1719 RGB images of EV batteries, and all screws in the images are manually labeled using LabelImg software. This dataset includes a total of 6992 external hex screws and 687 hex nuts.
- > The EV batteries image dataset (Part 2) includes 1159 RGB images of EV batteries, including image information of each stage of EV battery disassembly, for the identification and testing of various modules of EV batteries.
- > The EV batteries image dataset (Part 3) includes 1200 RGB images of EV batteries. All screws in the images are manually labeled using LabelImg software and classified based on the current disassembly state (whether the end effector is aligned, whether there are obstacles, etc.) for training neural predicate models.
- > The EV batteries image dataset (Part 4) includes 300 RGB images of common screws in EV batteries, and all screws in the images are manually labeled using LabelImg software. This dataset includes eight types of screws with different specifications, including external hexagonal screws, internal hexagonal screws, cross screws, and star screws.
Datasets and models of EV batteries for deep learning objects detection algorithms and positioning tasks.
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