Deep learning for credit card fraud detection: A review of algorithms, challenges, and solutions
Deep learning (DL), a branch of machine learning (ML), is the core technology in today's
technological advancements and innovations. Deep learning-based approaches are the …
technological advancements and innovations. Deep learning-based approaches are the …
How important are activation functions in regression and classification? A survey, performance comparison, and future directions
Inspired by biological neurons, the activation functions play an essential part in the learning
process of any artificial neural network (ANN) commonly used in many real-world problems …
process of any artificial neural network (ANN) commonly used in many real-world problems …
Graph neural network operators: a review
A Sharma, S Singh, S Ratna - Multimedia Tools and Applications, 2024 - Springer
Abstract Graph Neural Networks (GNN) is one of the promising machine learning areas in
solving real world problems such as social networks, recommender systems, computer …
solving real world problems such as social networks, recommender systems, computer …
Lstm-autoencoder for vibration anomaly detection in vertical carousel storage and retrieval system (vcsrs)
JS Do, AB Kareem, JW Hur - Sensors, 2023 - mdpi.com
Industry 5.0, also known as the “smart factory”, is an evolution of manufacturing technology
that utilizes advanced data analytics and machine learning techniques to optimize …
that utilizes advanced data analytics and machine learning techniques to optimize …
An n-sigmoid activation function to improve the squeeze-and-excitation for 2D and 3D deep networks
DB Mulindwa, S Du - Electronics, 2023 - mdpi.com
The Squeeze-and-Excitation (SE) structure has been designed to enhance the neural
network performance by allowing it to execute positive channel-wise feature recalibration …
network performance by allowing it to execute positive channel-wise feature recalibration …
Deep learning for echocardiography: Introduction for clinicians and future vision: State-of-the-art review
Exponential growth in data storage and computational power is rapidly narrowing the gap
between translating findings from advanced clinical informatics into cardiovascular clinical …
between translating findings from advanced clinical informatics into cardiovascular clinical …
Bi-directional long short term memory-gated recurrent unit model for Amharic next word prediction
The next word prediction is useful for the users and helps them to write more accurately and
quickly. Next word prediction is vital for the Amharic Language since different characters can …
quickly. Next word prediction is vital for the Amharic Language since different characters can …
Physics-informed deep learning for structural vibration identification and its application on a benchmark structure
Structural vibration identification is an important task in civil engineering that is based on
processing measured data from structural monitoring. However, predicting the response at …
processing measured data from structural monitoring. However, predicting the response at …
[HTML][HTML] Establishment of extensive artificial intelligence models for kinase inhibitor prediction: Identification of novel PDGFRB inhibitors
Identifying hit compounds is an important step in drug development. Unfortunately, this
process continues to be a challenging task. Several machine learning models have been …
process continues to be a challenging task. Several machine learning models have been …
Complex-valued trainable activation function hardware using a TCO/silicon modulator
Artificial neural network-based electro-optic chipsets constitute a very promising platform
because of its remarkable energy efficiency, dense wavelength parallelization possibilities …
because of its remarkable energy efficiency, dense wavelength parallelization possibilities …