Detection of Gender in Crowds Using ResNet Model

Deleted Journal, Journal Year: 2024, Volume and Issue: 20(2s), P. 389 - 408

Published: April 4, 2024

The ResNet model is used in this investigation to suggest a gender detection solution for use congested settings. Due occlusions, varied stances, and various features, determining person's crowded surroundings may be difficult time-consuming job. model, which deep convolutional neural network architecture, solve these difficulties because of its capacity capture detailed characteristics efficiency managing structures. strategy that has been suggested entails preprocessing the input photos, sending those images through then extracting gender-related from images. made up number residual blocks with skip connections, makes it easier learn complicated representations. After that, learnt are into fully linked layers, softmax activation determine subject's gender. usefulness technique was developed shown by experimental findings on large dataset, achieved high level accuracy determination. helps system handle scenarios improves system's ability accurately recognize situations people. method potential find applications areas such as surveillance, crowd control, study social behavior.

Language: Английский

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OxonFair: A Flexible Toolkit for Algorithmic Fairness

Published: Jan. 1, 2024

Language: Английский

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Are Fair Machine Learning Models More Useful?

Lecture notes in computer science, Journal Year: 2024, Volume and Issue: unknown, P. 38 - 53

Published: Jan. 1, 2024

Language: Английский

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