The final, formatted version of the article will be published soon. Objective This study aimed to assess the efficacy of intermittent theta burst stimulation (iTBS) applied to the lower limb motor ...

Understand what activation functions are and why they’re essential in deep learning! This beginner-friendly explanation covers popular functions like ReLU, Sigmoid, and Tanh—showing how they help ...

Explore 20 different activation functions for deep neural networks, with Python examples including ELU, ReLU, Leaky-ReLU, Sigmoid, and more. #ActivationFunctions #DeepLearning #Python As shutdown ...

ABSTRACT: Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving ...

Franco reaffirmed, "we said that we expected 2025 comparable FFO to be essentially flat compared to 2024 comparable FFO of $2.26 per share. This is still a good assumption as we sit here today." ...

ABSTRACT: We explore the performance of various artificial neural network architectures, including a multilayer perceptron (MLP), Kolmogorov-Arnold network (KAN), LSTM-GRU hybrid recursive neural ...

Introduction: Alzheimer’s disease (AD) has significant public health concerns in the aging society. AD can compromise brain function and lead to severe neurological abnormalities associated with ...

Activation functions play a critical role in AI inference, helping to ferret out nonlinear behaviors in AI models. This makes them an integral part of any neural network, but nonlinear functions can ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...