All the code and files related to the MI-Lab of UE19CS305 course in sem 5

Overview

Machine-Intelligence-Lab-CS305

The compilation of all the code an drelated files from MI-Lab UE19CS305 (of batch 2019-2023) offered by PES University

Instructions to run the code

  1. Enter the folder of the required week

  2. run the following command in the terminal:

    python3 SampleTest.py --SRN PES0UG00CS000

    where PES0UG00CS000 is the current file name in the repo for all the week code, change it accordingly

Note

  • Although most of the code is written independently, some weeks code are taken from others, feel free to let me know for credits if due.

  • Some of the code is written with the help of the internet and co-pilot, so the accuracy can't be guaranteed for all edge cases.

Owner
Arvind Krishna
Git, Set, Go
Arvind Krishna
PSANet: Point-wise Spatial Attention Network for Scene Parsing, ECCV2018.

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A benchmark dataset for mesh multi-label-classification based on cube engravings introduced in MeshCNN

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Apply a perspective transformation to a raster image inside Inkscape (no need to use an external software such as GIMP or Krita).

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A curated (most recent) list of resources for Learning with Noisy Labels

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[ICCV-2021] An Empirical Study of the Collapsing Problem in Semi-Supervised 2D Human Pose Estimation

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To build a regression model to predict the concrete compressive strength based on the different features in the training data.

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PyTorchVideo is a deeplearning library with a focus on video understanding work

PyTorchVideo is a deeplearning library with a focus on video understanding work. PytorchVideo provides resusable, modular and efficient components needed to accelerate the video understanding researc

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