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Visual Intelligence is a peer-reviewed journal published by Springer Nature, covering Multimodal Machine Learning Applications, Advanced Neural Network Applications, Video Surveillance and Tracking Methods.
| Publisher | Springer Nature |
|---|---|
| Reference style | Superscript numbered (Nature) Superscript — small raised numerals in the text 1. Smith, A., Jones, B. & Lee, C. A representative article title. Visual Intelligence 12, 45–58 (2023).
Formats any DOI in Visual Intelligence style. No sign-up. |
| Publishes research in | Multimodal Machine Learning Applications Advanced Neural Network Applications Video Surveillance and Tracking Methods Data Visualization and Analytics Human Pose and Action Recognition |
| ISSN | 2731-9008 |
| Citation impact (2-yr) | 11.23 |
| h-index | 21 |
| i10-index | 51 |
| Total citations | 1,557 |
| Open access | Yes |
| Top institutions publishing here | Sun Yat-sen University |
| 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.
Abstract Multimodal image fusion aims to integrate information from different imaging techniques to produce a comprehensive, detail-rich single image for downstream vision tasks. Existing methods based on local convolutional neural networks (CNNs) struggle to capture global features efficiently, while Transformer-based models are computationally expensive, although they excel at global modeling. Mamba addresses these limitations by…
Abstract Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive objects exhibiting camouflage. The current boom in terms of techniques and applications warrants an up-to-date survey. This can help researchers better understand the global CSU field, including both current achievements and remaining challenges. This paper makes four contributions: (1) For the…
Abstract In recent years, large-scale artificial intelligence (AI) models have become a focal point in technology, attracting widespread attention and acclaim. Notable examples include Google’s BERT and OpenAI’s GPT, which have scaled their parameter sizes to hundreds of billions or even tens of trillions. This growth has been accompanied by a significant increase in the…
Abstract Image segmentation plays an important role in vision understanding. Recently, the emerging vision foundation models continuously achieved superior performance on various tasks. Following such success, in this paper, we prove that the Segment Anything Model 2 (SAM2) can be a strong encoder for U-shaped segmentation models. We propose a simple but effective framework, termed…
Abstract Early detection and assessment of polyps play a crucial role in the prevention and treatment of colorectal cancer (CRC). Polyp segmentation provides an effective solution to assist clinicians in accurately locating and segmenting polyp regions. In the past, people often relied on manually extracted lower-level features such as color, texture, and shape, which often…
