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The effect of activation function choice on the performance of convolutional neural networks

Wang et al. | Sep 15, 2023

The effect of activation function choice on the performance of convolutional neural networks
Image credit: Tara Winstead

With the advance of technology, artificial intelligence (AI) is now applied widely in society. In the study of AI, machine learning (ML) is a subfield in which a machine learns to be better at performing certain tasks through experience. This work focuses on the convolutional neural network (CNN), a framework of ML, applied to an image classification task. Specifically, we analyzed the performance of the CNN as the type of neural activation function changes.

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OTGP: An innovative biometric authentication system with on-the-go passwords using a novel typing signature

Shirodkar et al. | Jun 08, 2026

OTGP: An innovative biometric authentication system with on-the-go passwords using a novel typing signature
Image credit: Shirodkar and Balasubramanian

This manuscript describes a new method of on-the-go passwords using typing characteristics. The authors developed a keyboard and keystroke recording setup and tested it with 30 participants. The results indicated the five chosen parameters are distinct across participants yet consistent across time for each participant, making it a plausible candidate for a behavior-based password system.

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Cleaning up the world’s oceans with underwater laser imaging

Gurbuz et al. | Jul 07, 2023

Cleaning up the world’s oceans with underwater laser imaging
Image credit: Naja Bertolt Jensen

Here recognizing the growing amount of plastic waste in the oceans, the authors sought to develop and test laser imaging for the identification of waste in water. They found that while possible, limitations such as increasing depth and water turbidity result in increasing blurriness in laser images. While their image processing methods were somewhat insufficient they identified recent methods to use deep learning-based techniques as a potential avenue to viability for this method.

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