Multimedia Systems

The Whole Slide Image (WSI) is a pathological image with Hematoxylin & Eosin staining. The low-contrast color staining will bring a challenge on analysis. We propose SNSeg (Staining Nuclear Segmentation) to improve the segmentation performance in ...

Currently, deep convolutional neural networks have made significant research progress in the field of underwater image enhancement and restoration. However, most of the existing methods use fixed-scale convolutional kernels, which are easily ...

The low-light image enhancement algorithm aims to solve the problem of poor contrast and low brightness of images in low-light environments. Although many image enhancement algorithms have been proposed, they still face the problems of loss of ...

Super-deformation in character design refers to a simplified modeling of character illustrations that are drawn in detail. Such super-deformation requires both texture and geometrical translation. However, directly adopting conventional image-to-...

The intricate architecture of gastric anatomy coupled with the complexities inherent in esophagogastroduodenoscopy (EGD) procedures can lead to blind spots during examinations. These blind spots refer to anatomical locations not visualized during ...

Accurate medical image segmentation can effectively assist disease diagnosis and treatment. While neural networks were often applied to solve the segmentation problem in recent computer-aided diagnosis, the metadata of patients was usually ...$$$$$$

Recommendation techniques play a vital role in recommending an actual product to an intended user. The recommendation also supports the user in the decision-making process. In recent years, collaborative filtering has been a widely used technique ...

Video semantic segmentation (VSS) plays a crucial role in various realistic applications, such as unmanned vehicles, autonomous robots, and augmented reality. Despite the significant progress achieved in this field, balancing accuracy and ...${}^{}$${}^{}$

The dynamical system perspective has been used to build efficient image classification networks and semantic segmentation networks. Furthermore, the Runge–Kutta (RK) methods are powerful tools for building networks from the dynamical systems ...

Deep learning-based automatic and accurate 3D pancreas segmentation plays a significant role in medical diagnosis and disease treatment, which has received a lot of attention from the medical image processing community. 3D pancreas segmentation ...

The image outpainting based on deep learning shows good performance and has a wide range of applications in many fields. The previous image outpainting methods mostly used a single image as input. In this paper, we use the left and right images as ...

Brain computed tomography (CT) report generation, which aims at generating accurate and descriptive reports for Brain CT imaging, has gained growing attention from researchers. Existing works mainly train a language-generation model with complex ...

Magnetic resonance (MR) imaging is widely used for assessing infant head and brain development and for diagnosing pathologies. The main goal of this work is the development of a segmentation framework to create patient-specific head and brain ...

Due to the expression of sharing information, there has been an increase in interest in safeguarding multimedia information and copyrights in recent times. Attackers are attempting to obtain sensitive information from a variety of sources, ...

Person re-identification (Re-ID) has long been a pressing challenge in the field of computer vision, with researchers primarily focusing on issues such as occlusion, clothing changes, and cross-modality scenarios. However, there has been a lack of ...

Transfer learning enables convolutional neural networks (CNN) to acquire knowledge from a source domain and transfer it to a target domain, where collecting large-scale annotated examples is time-consuming and expensive. Conventionally, while ...

Rescaling digital images for display on various devices, while simultaneously removing noise, has increasingly become a focus of attention. However, limited research has been done on a unified framework that can efficiently perform both tasks. In ...

Zero-shot image classification refers to the use of labeled images to train a classification model that can correctly classify images of unseen categories. Traditional zero-shot methods use attribute labels as supervisory information and map the ...

Children with autism face challenges in areas like language and social skills, which hinder their ability to undergo regular fire training. Fire is one of the most common and dangerous disaster in real life, making it essential to provide children ...

A major disease affecting individuals irrespective of the different ages is lung disease and this problem is a result of different causes. The recent spread of COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has ...

While the Transformer-based method has demonstrated exceptional performance in low-level visual processing tasks, it has a strong modeling ability only locally, thereby neglecting the importance of spatial feature information and high-frequency ...

This study concentrates on developing a mixed reality (MR) app for the historic ship Yavuz Battleship, also known as “SMS Goeben,” and assessing its acceptance using the technology acceptance model (TAM). Mixed reality blends real and virtual ...

In response to the problems of inaccurate feature alignment, loss of source domain information, imbalanced sample distribution, and biased class decision boundaries in traditional unsupervised domain adaptation methods, this paper proposes a class ...

The past decade has seen significant advancements in computer vision technologies, resulting in an increasing consumption of images and videos by both human and machine. Although machines are usually the primary consumers, there are many ...$$

Iris recognition models that can be deployed on mobile devices have further requirements for both model scale and accuracy. We note that iris segmentation and localization tasks are the basis of iris recognition. Therefore, to better meet the ...

The coronavirus diseases (COVID-19) are transmittable diseases which are caused by Severe Acute Respiratory Syndrome human coronavirus (SARS-CoV). This paper describes the identification of coronavirus disease infections and better treatments ...

Driver intention prediction allows drivers to perceive possible dangers in the fastest time and has become one of the most important research topics in the field of self-driving in recent years. In this study, we propose a driver intention ...

The non-local means (NLM) algorithm is a classical image denoising algorithm. However, the denoising effect of the NLM algorithm is easily affected by the noise level of neighboring pixels, which leads to poor denoising effect for high noise level ...

To fully exploit the multiscale information for image denoising, we introduce the idea of full-scale skip connections in the image segmentation network UNet3+. However, existing UNet3+ networks aggregate multiscale information by directly ...

Due to the distortion of projection generated during the production of ${360}^{\circ }$ video, most quality assessment algorithms used for 2D video have the problem of performance degradation. In this paper, we propose a full-reference ${360}^{\circ }$ video quality ...${\mathrm{}}^{}$${\mathrm{}}^{}$