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Everything about Neural network software
Type of software
Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural networks, and in some cases, a wider array of adaptive systems such as artificial intelligence and machine learning. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Neural network softwareA 5-minute orientation
- Skim a recent paper: Hybrid Optimization-Based Neural Network Classifier for Software Defect PredictionInfluential work since 2022
- Pick up a classic book: Spiking neuron modelsThe most-reprinted book on the subject
- Read the landmark paper: Software defect prediction using cost-sensitive neural networkCited 222 times
- Go sideways: NeuroSolutionsA closely related topic
- Go sideways: Peltarion SynapseA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Software defect prediction using cost-sensitive neural network
Effective Software Fault Localization Using an RBF Neural Network
Deep neural network based hybrid approach for software defect prediction using software metrics
On the neural network approach in software reliability modeling
Predicting software reliability with neural network ensembles
An enhanced neural network technique for software risk analysis
Software Defect Prediction via Attention-Based Recurrent Neural Network
Using a neural network in the software testing process
🆕 Influential since 2022
Hybrid Optimization-Based Neural Network Classifier for Software Defect Prediction
Software defect prediction via optimal trained convolutional neural network
A Neural Network Approach for Software Reliability Prediction
The application of neural network for software vulnerability detection: a review
Software Fault Localization Based on Network Spectrum and Graph Neural Network
📚 Books worth reading
Spiking neuron modelsWulfram Gerstner, Werner M. Kistler · 2002
Optical networksRajiv Ramaswami, Kumar Sivarajan · 1998
Python machine learningSebastian Raschka · 2015
Advances in Neural Networks - ISNN 2007Derong Liu · 2007
Soft ComputingFred Aminzadeh · 1994
Advances in neural networks--ISNN 2004International Symposium on Neural Networks (2004 Dalian, Liaoning Sheng, China) · 2004
Emergent neural computational architectures based on neuroscienceStefan Wermter, David J. Willshaw · 2001
Methods and models in artificial and natural computationInternational Work-Conference on the Interplay Between Natural and Artificial Computation (3rd 2009 Santiago de Compostela, Spain) · 2009
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- NeuroSolutions NeuroSolutions is a neural network development environment developed by NeuroDimension. It combines a modular, icon-based (component-based) network design…
- Peltarion Synapse Synapse is a component-based development environment for neural networks and adaptive systems. Created by Peltarion, Synapse allows data mining, statistical…
- Emergent (software) Emergent (formerly PDP++) is a biologically-based neural simulation software that is primarily intended for creating models of the brain and cognitive…
- Predictive Model Markup Language The Predictive Model Markup Language (PMML) is an XML-based predictive model interchange format conceived by Robert Lee Grossman, then the director of…
- Orange (software) Orange is an open-source software package for data visualization, machine learning, data mining, and data analysis. It provides a visual programming environment…
- Bio-inspired computing Bio-inspired computing, short for biologically inspired computing, is a field of study which seeks to solve computer science problems using models of biology…
- Nervous system network models The network of the human nervous system is composed of nodes (for example, neurons) that are connected by links (for example, synapses). The connectivity…
- GENESIS (software) GENESIS (The General Neural Simulation System) is a simulation environment for constructing realistic models of neurobiological systems at many levels…