ISSN: 2162-237X

Journal Home

Journal Guideline

IEEE Transactions on Neural Networks and Learning Systems Q1 Unclaimed

IEEE Computational Intelligence Society United States

Unfortunately this journal has not been claimed yet. For this reason, some information may be unavailable.

IEEE Transactions on Neural Networks and Learning Systems is a journal indexed in SJR in Software and Computer Science Applications with an H index of 221. It has an SJR impact factor of 4.222 and it has a best quartile of Q1. It has an SJR impact factor of 4.222.

IEEE Transactions on Neural Networks and Learning Systems focuses its scope in these topics and keywords: neural, learning, network, data, multiple, classification, dynamic, linear, learningearly, label, ...

Type: Journal

Type of Copyright:

Languages:

Open Access Policy:

Type of publications:

Publication frecuency: -

Categories: Artificial Intelligence (Q1) Computer Networks and Communications (Q1) Computer Science Applications (Q1) Software (Q1)

Price

- €

Inmediate OA

NPD

Embargoed OA

- €

Non OA

Metrics

IEEE Transactions on Neural Networks and Learning Systems

4.222

SJR Impact factor

221

H Index

1317

Total Docs (Last Year)

1358

Total Docs (3 years)

23530

Total Refs

15011

Total Cites (3 years)

1349

Citable Docs (3 years)

10.47

Cites/Doc (2 years)

17.87

Ref/Doc

Comments

No comments ... Be the first to comment!

Publication speed *

Review quality *

Edition and editorial team *

Institutional email or ORCID *

* The email or ORCID field is only to validate the authenticity of the comment, the identity will not be public. .

Other journals with similar parameters

IEEE Transactions on Pattern Analysis and Machine Intelligence Q1
International Journal of Computer Vision Q1
IEEE Transactions on Evolutionary Computation Q1
IEEE Network Q1
Information Fusion Q1

Compare this journals

Aims and Scope

Best articles by citations

Stochastic Stability of Delayed Neural Networks With Local Impulsive Effects

Singularities of Three-Layered Complex-Valued Neural Networks With Split Activation Function

Error Analysis for Matrix Elastic-Net Regularization Algorithms

Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks

3-D Quasi-Recurrent Neural Network for Hyperspectral Image Denoising

Discrete-Time Local Value Iteration Adaptive Dynamic Programming: Admissibility and Termination Analysis

Fault Identification in Distributed Sensor Networks Based on Universal Probabilistic Modeling

Context Dependent Encoding Using Convolutional Dynamic Networks

Greedy Methods, Randomization Approaches, and Multiarm Bandit Algorithms for Efficient Sparsity-Constrained Optimization

First-Spike-Based Visual Categorization Using Reward-Modulated STDP

Automatic Face Naming by Learning Discriminative Affinity Matrices From Weakly Labeled Images

Solving Partial Least Squares Regression via Manifold Optimization Approaches

SHOW MORE ARTICLES

Extreme Learning Machine With Affine Transformation Inputs in an Activation Function

Autoencoder Constrained Clustering With Adaptive Neighbors

Improving the Quality of Self-Organizing Maps by Self-Intersection Avoidance

Domain-Weighted Majority Voting for Crowdsourcing

Naive Gabor Networks for Hyperspectral Image Classification

Feedback Solution to Optimal Switching Problems With Switching Cost

Evolving Deep Neural Networks via Cooperative Coevolution With Backpropagation

Robust One-Class Kernel Spectral Regression

Hyperparameter Selection for Gaussian Process One-Class Classification

Inverting the Generator of a Generative Adversarial Network

Fast Neuromimetic Object Recognition Using FPGA Outperforms GPU Implementations

Diverse Instance-Weighting Ensemble Based on Region Drift Disagreement for Concept Drift Adaptation