Multimedia Tools and Applications

The convolutional residual tracking networks (CREST) uses a single-layer convolutional network as the implicit correlation filter, which can perform end-to-end training and has the advantages of simple model structure and high tracking accuracy. ...

CNN is inspired from Primary Visual (V1) neurons. It is a typical deep learning technique and can help teach machine how to see and identify objects. In the most recent decade, deep learning develops rapidly and has been well used in various ...

Aiming at the research of real-time data transmission and multi-scale image decomposition of embedded optical sensor array, the principle, method and fusion strategy of multi-sensor image fusion are studied comprehensively, thoroughly and ...

Stroke is enlisted as one of the leading causes of death and serious disability affecting millions of human lives across the world with high possibilities of becoming an epidemic in the next few decades. Timely detection and prompt decision making ...

The availability of the system is one of the main requirements of a multimedia-based e-health application that carries critical patient health information in the network environment. On the other hand, the Distributed Denial of Service (DDoS) ...

Computer-aided diagnosis has attracted attention for the accurate grading of cerebral glioma. Most algorithms are only effective in relatively large datasets. Although multicenter data sharing is expanding, the results of cerebral glioma grading ...

Osteoarthritis (OA) is a common form of knee arthritis which causes significant disability and is threatening to plague patient’s quality of life. Although this chronic condition does not lead to fatality, still there exists no known cure for OA. ...

Chronic diseases (such as diabetes, hypertension, etc) are generally of long duration and slow progression. These diseases may be implied in electronic medical records (EMR), and one chronic disease may be accompanied by another. Recently, many ...

The irrelevant background information in the personalized image is easy to be quantified into the same word as the main target, and the quantization process will inevitably cause the loss of a lot of visual information. This phenomenon will ...

Medical images with various modalities have become an integral part of the diagnosis and treatment of several diseases. The medical practitioners often use previous case studies to deal with the current medical condition of any particular patient. ...

Early detection of malignant skin lesions improves patient survival rates. Conventional self-detection method for public invariably suffers from limitations: subjectivity, inaccuracy, and expert dependent variability. Therefore, this study ...

Extreme learning machine (ELM) is a training algorithm for single hidden layer feedforward neural network (SLFN), which converges much faster than traditional methods and yields promising performance. In this paper, we hope to present a ...

Three dimensional (3D) hand pose estimation is the task of estimating the 3D location of hand keypoints. In recent years, this task has received much research attention due to its diverse applications in human-computer interaction and virtual ...

This paper researches how to use attention mechanism to fuse the time series information of facial expression and speech, and proposes a multi-modal feature fusion emotion recognition model based on attention mechanism. First, facial expression ...

A convenient, accurate and well-known way toward any supervised task is using Nearest Neighbor approach or its variants. However, there has been little attempt toward improving interpretability by human and providing a classical optimization of ...

The main objective of this paper is to develop an interactive classifier aided deep learning system to assist cardiologists for heart arrhythmia disease classification as it shows a health-threatening condition that can lead to heart-related ...

EEG signal classification is a key technology for EEG signal processing and identification systems. Dictionary learning has shown excellent performance due to its sparse representation and learning capability. Usually dictionary learning requires ...

The denoising of brain magnetic resonance images could be important for the medical image analysis. Many algorithms have been proposed for this task, especially the deep learning ones which show great success compared with the classical image ...

Optical coherence tomography (OCT) is a non-invasive technique to capture cross-sectional volumes of the human retina. OCT images are used for the diagnosis of various ocular diseases. However, OCT datasets generally suffer from the problem of ...

Breast cancer rates are rising. It also remains the second principal reason for cancer-related mortality in females, and the mortality rate is also drastically rising. In recent years, MicroRNAs (miRNAs) have emerged to have a large potential as ...

The current study of kidney stones made by the National Health and Nutrition Examination Survey (NHANES) describes that over the last eighty years the number of stones present in the kidney is significantly enhanced by approximately 70% (2015). ...

Infrared Hyperthermia therapy (IHT) is a non-contacting method to elevate body temperature and treat malignant lesions such as breast cancer. Breast cancer is one of the major cancer types among females and over the years, its prevalence is ...

Due to the magnification of X-ray images, calibration is required for recording linear measurements. Clinically, calibration can be performed on a lateral X-ray image, but it is difficult to perform on the PA (posteroanterior) X-ray image due to ...

Postpartum haemorrhage is a type of blood loss that occurs after the birth of a baby. When you lose more than 500 ml of blood, your blood pressure drops, and you may suffer and die as a result. Deep learning techniques can predict postpartum ...

In the Internet of Medical Things (IoMT), collaboration among institutes can help complex medical and clinical analysis of disease. Deep neural networks (DNN) require training models on large, diverse patients to achieve expert clinician-level ...

Retinal images are playing a very significant role in medical imaging technology. The variation in blood vessel attributes like tortuosity, focal length, branching angle, deformations like haemorrhage, lesions, etc. are good indicators of many ...

Using an image compression hybrid model, the suggested research created a practical method for integrating learning system advantages with a decision logic framework. The emphasis here is that when integrated with the conventional image coding ...

The blood-oxygen label dependent (BOLD) signal obtained from functional magnetic resonance images (fMRI) varies significantly among populations. Yet, there is some agreement among researchers over the pace of the blood flow within several brain ...