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Top Transverse Computer Vision Models
The models below have been fine-tuned for various transverse detection tasks. You can try out each model in your browser, or test an edge deployment solution (i.e. to an NVIDIA Jetson). You can use the datasets associated with the models below as a starting point for building your own transverse detection model.
At the bottom of this page, we have guides on how to count transverses in images and videos.
by system zoon
9323 images 15 classes
人手孔高差-(Manhole-and-Handhole-Height-Difference) 冒油-(Oil-Bleeding) 剝落-(Delamination) 坑洞-(Potholes) 塊狀裂縫-(Block-Cracking) 推擠-(Shoving) 橫/縱向裂縫-(Transverse/Longitudinal-Cracking) 波浪型鋪面-(Corrugation) 滑溜裂縫-(Slippery-Cracks) 薄層剝離-(Thin-Layer-Stripping) 補綻-(Patch-Distress) 車轍-(Ruts) 車道與路肩分離-(Separation-of-Lane-and-Shoulder) 隆起與凹陷-(Bumps-and-Sags) 鱷魚狀裂縫-(Alligator-Cracking)
by Test
131 images 3 classes
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