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This lIBeginnerls Guide to PROCSYll. presents an annotated example of. the use of the Purdue ~emote On~Line £onsole System, (PROCSY) which is the terminal system provided by the Purdue University Computi.ng Center.

We demonstrate its use by generating ProcSy, a synthetic dataset for semantic segmentation, which is modeled on a real-world urban environment and features a range of variable influence factors, such as weather and lighting.

We demonstrate its use by generating ProcSy (pronounced "proxy"), a synthetic dataset for semantic segmentation, which is modeled on a real-world urban environment and features a range of variable influence factors, such as weather and lighting. Our experiments investigate impact of the factors on performance of a state-of-the-art deep network.

We demonstrate its use by generating ProcSy, a synthetic dataset for semantic segmentation, which is modeled on a real-world urban environment and features a range of variable influence factors, such as weather and lighting.

We present a novel workflow to replicate a real-world operational design domain in order to generate a semantic segmentation dataset with weather and lighting variations. We generate a sample synthetic dataset, ProcSy, con-sisting of 11,000 unique image frames that represent a 3 km2 area of urban Canada (Fig. 1).

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