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IEEE Transactions on Emerging Topics in Computational Intelligence is a peer-reviewed journal published by IEEE, covering Big Data and Digital Economy, Neural Networks and Applications, Metaheuristic Optimization Algorithms Research. Over its lifetime it has published 1,754 papers, which have received 28,221 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," IEEE Transactions on Emerging Topics in Computational Intelligence, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in IEEE Transactions on Emerging Topics in Computational Intelligence style. No sign-up. |
| Abbreviation (ISO-4) | TETCI |
| Publishes research in | Big Data and Digital Economy Neural Networks and Applications Metaheuristic Optimization Algorithms Research Advanced Multi-Objective Optimization Algorithms Anomaly Detection Techniques and Applications |
| ISSN | 2471-285X |
| Citation impact (2-yr) | 5.33 |
| h-index | 71 |
| i10-index | 623 |
| Top institutions publishing here | South China University of Technology |
| Journal website | ieeexplore.ieee.org |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Network intrusion detection systems (NIDSs) play a crucial role in defending computer networks. However, there are concerns regarding the feasibility and sustainability of current approaches when faced with the demands of modern networks. More specifically, these concerns relate to the increasing levels of required human interaction and the decreasing levels of detection accuracy. This paper…
A field that has directly benefited from the recent advances in deep learning is automatic speech recognition (ASR). Despite the great achievements of the past decades, however, a natural and robust human-machine speech interaction still appears to be out of reach, especially in challenging environments characterized by significant noise and reverberation. To improve robustness, modern…
Traditional optimization solvers tend to start the search from scratch by assuming zero prior knowledge about the task at hand. Generally speaking, the capabilities of solvers do not automatically grow with experience. In contrast, however, humans routinely make use of a pool of knowledge drawn from past experiences whenever faced with a new task. This…
Accurate segmentation of organs or lesions from medical images is crucial for reliable diagnosis of diseases and organ morphometry. In recent years, convolutional encoder-decoder solutions have achieved substantial progress in the field of automatic medical image segmentation. Due to the inherent bias in the convolution operations, prior models mainly focus on local visual cues formed…
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