International Journal of Neural Systems 
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This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.A Parallel Convolutional Network Based on Spiking Neural Systems
Int J Neural Syst. 2024 Mar 15:2450022. doi: 10.1142/S0129065724500229. Online ahead of print.ABSTRACTDeep convolutional neural networks have shown advanced performance in accurately segmenting images. In this paper, an SNP-like convolutional neuron structure is introduced, abstracted from the nonlinear mechanism in nonlinear spiking neural P (NSNP) systems. Then, a U-shaped convolutional neural network named SNP-like parallel-convolutional network, or SPC-Net, is constructed for segmentation tasks. The dual-convolution concatenate (DCC) and dual-convolution addition (DCA) network blocks are designed, respectively, in the ...
Source: International Journal of Neural Systems - March 15, 2024 Category: Neurology Authors: Chi Zhou Lulin Ye Hong Peng Zhicai Liu Jun Wang Antonio Ram írez-De-Arellano Source Type: research
An Asynchronous Spiking Neural Membrane System for Edge Detection
Int J Neural Syst. 2024 Mar 16:2450023. doi: 10.1142/S0129065724500230. Online ahead of print.ABSTRACTSpiking neural membrane systems (SN P systems) are a class of bio-inspired models inspired by the activities and connectivity of neurons. Extensive studies have been made on SN P systems with synchronization-based communication, while further efforts are needed for the systems with rhythm-based communication. In this work, we design an asynchronous SN P system with resonant connections where all the enabled neurons in the same group connected by resonant connections should instantly produce spikes with the same rhythm. In ...
Source: International Journal of Neural Systems - March 15, 2024 Category: Neurology Authors: Luping Zhang Fei Xu Ferrante Neri Source Type: research
Edge Computing Transformers for Fall Detection in Older Adults
Int J Neural Syst. 2024 Mar 16:2450026. doi: 10.1142/S0129065724500266. Online ahead of print.ABSTRACTThe global trend of increasing life expectancy introduces new challenges with far-reaching implications. Among these, the risk of falls among older adults is particularly significant, affecting individual health and the quality of life, and placing an additional burden on healthcare systems. Existing fall detection systems often have limitations, including delays due to continuous server communication, high false-positive rates, low adoption rates due to wearability and comfort issues, and high costs. In response to these ...
Source: International Journal of Neural Systems - March 15, 2024 Category: Neurology Authors: Jes ús Fernandez-Bermejo Jes ús Martinez-Del-Rincon Javier Dorado Xavier Del Toro Mar ía J Santofimia Juan C Lopez Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Modular Spiking Neural Membrane Systems for Image Classification
Int J Neural Syst. 2024 Mar 8:2450021. doi: 10.1142/S0129065724500217. Online ahead of print.ABSTRACTA variant of membrane computing models called Spiking Neural P systems (SNP systems) closely mimics the structure and behavior of biological neurons. As third-generation neural networks, SNP systems have flexible architectures allowing the design of bio-inspired machine learning algorithms. This paper proposes Modular Spiking Neural P (MSNP) systems to solve image classification problems, a novel SNP system to be applied in scenarios where hundreds or even thousands of different classes are considered. A main issue to face ...
Source: International Journal of Neural Systems - March 7, 2024 Category: Neurology Authors: Iris Ermini Claudio Zandron Source Type: research
Robust Federated Learning for Heterogeneous Model and Data
Int J Neural Syst. 2024 Apr;34(4):2450019. doi: 10.1142/S0129065724500199. Epub 2024 Feb 19.ABSTRACTData privacy and security is an essential challenge in medical clinical settings, where individual hospital has its own sensitive patients data. Due to recent advances in decentralized machine learning in Federated Learning (FL), each hospital has its own private data and learning models to collaborate with other trusted participating hospitals. Heterogeneous data and models among different hospitals raise major challenges in robust FL, such as gradient leakage, where participants can exploit model weights to infer data. Her...
Source: International Journal of Neural Systems - February 28, 2024 Category: Neurology Authors: Hussain Ahmad Madni Rao Muhammad Umer Gian Luca Foresti Source Type: research
Enhanced Multitask Learning for Hash Code Generation of Palmprint Biometrics
Int J Neural Syst. 2024 Apr;34(4):2450020. doi: 10.1142/S0129065724500205. Epub 2024 Feb 19.ABSTRACTThis paper presents a novel multitask learning framework for palmprint biometrics, which optimizes classification and hashing branches jointly. The classification branch within our framework facilitates the concurrent execution of three distinct tasks: identity recognition and classification of soft biometrics, encompassing gender and chirality. On the other hand, the hashing branch enables the generation of palmprint hash codes, optimizing for minimal storage as templates and efficient matching. The hashing branch derives t...
Source: International Journal of Neural Systems - February 28, 2024 Category: Neurology Authors: Lin Chen Lu Leng Ziyuan Yang Andrew Beng Jin Teoh Source Type: research
Robust Federated Learning for Heterogeneous Model and Data
Int J Neural Syst. 2024 Apr;34(4):2450019. doi: 10.1142/S0129065724500199. Epub 2024 Feb 19.ABSTRACTData privacy and security is an essential challenge in medical clinical settings, where individual hospital has its own sensitive patients data. Due to recent advances in decentralized machine learning in Federated Learning (FL), each hospital has its own private data and learning models to collaborate with other trusted participating hospitals. Heterogeneous data and models among different hospitals raise major challenges in robust FL, such as gradient leakage, where participants can exploit model weights to infer data. Her...
Source: International Journal of Neural Systems - February 28, 2024 Category: Neurology Authors: Hussain Ahmad Madni Rao Muhammad Umer Gian Luca Foresti Source Type: research
Enhanced Multitask Learning for Hash Code Generation of Palmprint Biometrics
Int J Neural Syst. 2024 Apr;34(4):2450020. doi: 10.1142/S0129065724500205. Epub 2024 Feb 19.ABSTRACTThis paper presents a novel multitask learning framework for palmprint biometrics, which optimizes classification and hashing branches jointly. The classification branch within our framework facilitates the concurrent execution of three distinct tasks: identity recognition and classification of soft biometrics, encompassing gender and chirality. On the other hand, the hashing branch enables the generation of palmprint hash codes, optimizing for minimal storage as templates and efficient matching. The hashing branch derives t...
Source: International Journal of Neural Systems - February 28, 2024 Category: Neurology Authors: Lin Chen Lu Leng Ziyuan Yang Andrew Beng Jin Teoh Source Type: research
Robust Federated Learning for Heterogeneous Model and Data
Int J Neural Syst. 2024 Apr;34(4):2450019. doi: 10.1142/S0129065724500199. Epub 2024 Feb 19.ABSTRACTData privacy and security is an essential challenge in medical clinical settings, where individual hospital has its own sensitive patients data. Due to recent advances in decentralized machine learning in Federated Learning (FL), each hospital has its own private data and learning models to collaborate with other trusted participating hospitals. Heterogeneous data and models among different hospitals raise major challenges in robust FL, such as gradient leakage, where participants can exploit model weights to infer data. Her...
Source: International Journal of Neural Systems - February 28, 2024 Category: Neurology Authors: Hussain Ahmad Madni Rao Muhammad Umer Gian Luca Foresti Source Type: research
