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The Segment Anything Model (SAM) has garnered significant attention due to its superior zero-shot generalization ability. However, the development of SAM in medical image segmentation continues to confront challenges related to data sharing ...

The environmental issues brought on by carbon emissions from transport have risen to prominence in recent years. More and more academics are using the multi‐objective path optimization method to solve the multimodal optimization problem from the ...

In order to reduce the complexity of multimodal transportation path optimization and solve the convergence of multi‐objective optimization. A two‐stage algorithm is proposed for research. In the first stage, a fuzzy C‐clustering model is established to ...

High dropout rates are a major challenge for Massive Open Online Courses (MOOCs), making dropout prediction a crucial task. Existing research often develops various prediction models based on student behavioral features. However, most of the ...

Text segmentation is a crucial aspect of various text-related tasks, including text erasing, text editing, and font style transfer. In recent years, multiple text segmentation datasets, such as TextSeg focusing on Latin text segmentation and BTS on ...

Multiple object tracking (MOT) tends to become more challenging when severe occlusions occur. In this paper, we analyze the limitations of traditional Convolutional Neural Network-based methods and Transformer-based methods in handling occlusions and ...

In order to address the issue of the existing motion vector-based video reversible information hiding algorithms, which are unable to adaptively adjust the embedding capacity based on the visual characteristics of video frames and have limited capacity, ...

Prediction for Intensive Care Unit (ICU) readmission is conducive to assisting doctors in treatment-related decision making and reducing the risk of relapse after discharge. Recently, existing ICU readmission prediction approaches train each sub-...

In recent years, Massive Open Online Courses (MOOCs) have become the main online learning method for students all over the world, but their development has been affected by the high dropout rate for a long time. Therefore, dropout prediction is a ...

Cost assignment in the motion vector domain remains a research focus in video steganography. Recent studies in image steganography have summarized many principles for cost assignment and achieved good results. But the basic principles for cost ...

Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the diagnosis of neurological diseases such as epilepsy, Alzheimer’s, and multiple sclerosis. Recently, UNet-like architectures are widely ...

• We propose a purification component DPSB (Dilate Pyramid Separate Block).
• We ...

The goal of the diagnostic prediction task is to predict what disease patients are likely to have at their next visit, based on their historical electronic medical records. Existing studies mainly conduct the prediction task by separately using discrete ...

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• To predict mortality with fusion of sequential visits and medical ontology.
• To ...

The goal of mortality prediction task is to predict the future death risk of patients according to their previous Electronic Healthcare Records (EHR). The main challenge of mortality prediction is how to design an accurate and robust ...

Cloud storage and cloud computing technologies have developed rapidly for a long time, and many users outsource the storage burden of their data to the cloud to obtain more convenient cloud storage services. Allowing users to audit the private data’s ...

Steganography is a popular research direction in the field of information security. Due to the widespread use of video media, video steganography has received much attention from the research community. Among video steganography, motion vector (MV)-based ...

Predicting the readmission risk within 30 days on the Electronic Health Record (EHR) has been proven crucial for predictive analytics in healthcare domain. Deep-learning-based models are recently utilized to address this task since those models ...

Complexity of emergency procedures have direct impacts on the accomplishment of tasks in metro system. In order to ensure the efficient operation of automated metro in emergency scenarios, it is necessary to understand the potential relationship between ...

Autism spectrum disorder (ASD) is a developmental disorder that impacts more than 1.6% of children aged 8 across the United States. It is characterized by impairments in social interaction and communication, as well as by a restricted repertoire of ...

Accessible design of railway vehicles is a public safety concern. As a formative approach of work analysis, Cognitive Work Analysis (CWA) is applied in this paper to better understand the accessible design constrains and cognitive behavior of barrier-free ...

In this paper, we focus on detecting highlights in online videos. Given the explosive growth of online videos, it is becoming increasingly important to single out those highlights for audiences instead of requiring them browsing every tedious part ...

Histogram modification (HM) is an efficient algorithm for reversible data hiding into H.264 video, motion vector based methods have been applied to HM. In this paper, we present a special strategy of reversible data hiding using motion vector based on ...