📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

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Deep Learningcomputer-visiondeep-learningmetricsdnnpytorchcomparisonpytorch-implementation
Overview

Weird Deep Learning Metrics

📚 A collection of all the Deep Learning Metrics that I came across which are not accuracy/loss.

Metric Description Notes
Churn Shows the disagreement between two model's prediction. Higher the churn, more the disagreement. Bounds: [0,1]. Takes two prediction arrays as inputs and retuns churn percentage. From this paper
Owner
Rahul Vigneswaran
Rahul Vigneswaran
GitHub Repository
Detectron2 is FAIR's next-generation platform for object detection and segmentation.

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Computer vision - fun segmentation experience using classic and deep tools :)

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This is an open source python repository for various python tests

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Contrastive Learning Inverts the Data Generating Process

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VOLO: Vision Outlooker for Visual Recognition

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Pgn2tex - Scripts to convert pgn files to latex document. Useful to build books or pdf from pgn studies

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MetaShift: A Dataset of Datasets for Evaluating Contextual Distribution Shifts and Training Conflicts (ICLR 2022)

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Official implementation of NPMs: Neural Parametric Models for 3D Deformable Shapes - ICCV 2021

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MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification

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An implementation of the research paper "Retina Blood Vessel Segmentation Using A U-Net Based Convolutional Neural Network"

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An implementation for the loss function proposed in Decoupled Contrastive Loss paper.

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CFC-Net: A Critical Feature Capturing Network for Arbitrary-Oriented Object Detection in Remote Sensing Images

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DECAF: Deep Extreme Classification with Label Features

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