Multimedia Tools and Applications

This paper suggests novel cancellable biometric realization approach recognition and template protection. In this paper, the Homomorphic Filtering Masking (HFM) encoding algorithm is utilized for cancelable palmprint recognition system. In the ...

Skin malignant growth has been regarded as the most widely recognized disease in the world and Malignant Melanoma is one of the deadliest diseases of skin cancer. Early prediction can be helpful to avoid the damage of this disease, however, many ...

Existing deep learning models have made some progress in improving detection accuracy for small objects, but there remains much work to be done in coordinating the practical factors involved in real object detection: accuracy, running time, model ...

Image denoising techniques are very important in modern digital image processing. Many classical denoising algorithms have evolved over the years, such as Butterworth filter, Mean filter, Median filter, Laplacian filter, Multidimensional filter, ...

Owing to the low brightness, low contrast, and high labeling difficulty of night-time vehicle images, night-time vehicle model recognition (NVMR) faces significant challenges. To address these challenges, this paper proposes the Night-time Vehicle ...

Wheat is an important grain in the food chain. It is important in terms of efficiency and economy to use wheat in the appropriate area according to its varieties. Breeding studies make varieties of wheat physically similar to each other and make ...

Personalized clothing recommendation remains challenging due to the richness of fashion item representations, the non-uniqueness of fashion compatibility relationship and the complicated conditions of user preference. To address these problems, a ...

Non-negative Tucker decomposition (NTD) is a powerful tool for data representation to capture rich internal structure information from non-negative high-dimensional tensor data. Arguing that NTD methods often give global-like information, graph ...

Glaucoma is one of the world leading causes of irreversible blindness. Early detection is essential to delay its progression and prevent vision loss. An accurate segmentation of the cup region in retinal fundus images is necessary to obtain ...

Deep learning has become ubiquitous in the field of computer vision for tasks such as image classification and segmentation. A Computer-Aided Diagnostic (CAD) system for lung cancer detection and diagnosis works by identifying lung nodules and ...

Security and confidentiality are one of the main concerns when transmitting multimedia data over the Internet. To deal with the arising security issues, many advanced cryptographic algorithms have been proposed in the literature. The efficiency of ...

The problem of solving the nonlinear equations in the range-free localization algorithm has been transformed into an optimal solution problem. Meta-heuristic optimization method has been widely adopted to tackle above issues. How to choose the ...

Recognizing emotions from physiological signals has proven to be important in various scenarios. To assist in developing emotion recognizers, software frameworks and toolboxes have emerged, offering ready-to-use components. However,these have ...

The traditional Local Binary Pattern (LBP) employs a 3x3 pixel window and examines the intensity differences between the center pixel and nearby neighbourhood pixels. However, LBP excludes the magnitude of difference information entirely, which ...

Reversible data hiding (RDH) technique has been widely used for content authentication. However, most conventional RDH schemes generally concentrates on the rate-and-distortion performance (namely high capacity and low distortion), instead of ...

Crowdsourcing is a process of engaging a ‘crowd’ or a group of common people for accomplishing the tasks. In this work, the time-bound tasks allocation problem in IoT-based crowdsourcing is investigated in strategic setting. The proposed model ...

Parts-of-Speech (POS) Tagging is one of the fundamental and pre-processing steps for Natural Language Processing (NLP) tasks such as Text Summarization, Name Entity Recognition, Dependency Parsing or Parsing in general, Classification, Sentiment ...$\mathrm{}$

This article proposes a hybrid network model for video-based human facial expression recognition (FER) system consisting of an end-to-end 3D deep convolutional neural networks. The proposed network combines two commonly used deep 3-dimensional ...

In this paper, we propose a method for abnormal event detection in videos based on Multi-scale Pyramid Grid Templates (MPGT). Unlike traditional methods that usually finish anomaly detection based on a single scale feature, we propose to detect ...

Forged images in JPEG format have a ubiquitous presence in today’s world due to the ease of availability of image manipulation tools. This paper presents a deep learning-based system that utilizes the inherent relationship between histograms of ...$\mathrm{}\mathrm{}$$\mathrm{}\mathrm{}$$\mathrm{}\mathrm{}$

In many countries, agriculture plays a major role in the economy. The health of the crop is therefore very important, but there are many plant diseases that are difficult to diagnose. A close inspection is necessary in many cases, or an expert’s ...

The world we live in is dynamic by nature. Frequently, the environment changes in ways we cannot predict. In machine learning, the phenomenon that occurs when a model has its prediction effectiveness degraded due to unforeseen changes is known as ...

Information security is very important in the era of rapid development of science and technology. People often use multimedia to communicate in their daily life. Image plays an important role in multimedia communication, so it is urgent to protect ...

The growing availability of applications (apps) for smart gadgets has been phenomenal in recent years. Both independent developers and multinational corporations are working to boost their app ratings in order to stay competitive in the mobile app ...

In recent years deep learning (DL) models have obtained great success in hyperspectral image classification (HSIC) with commendable performance and especially convolutional neural networks (CNNs) have attracted huge attention due to the ...

In the field of high-resolution tomography, there is currently a notable increase in the volume of tomographic projections and data produced. Such a context has been demanding new computational approaches to the process of reconstruction and ...

In this paper, we address special scenario makeup-transfer tasks designed to transfer makeup features from a low-resolution (LR) reference image to a LR source image and generate high-resolution (HR) results. Existing methods are not suitable when ...

Object detection is one of the most basic and important research tasks in the field of computer vision. The general trend in object detection has been to design large and over-parameterized models, which can achieve excellent performance. However, ...

Music genre classification (MGC) is an indispensable branch of music information retrieval. With the prevalence of end-to-end learning, the research on MGC has made some breakthroughs. However, the limited receptive field of convolutional neural ...

Object detection of continuous sonar image sequences has become an efficient way for underwater environment exploration. However, the task always suffers from the influence of th e complex underwater environment. In particular, the existing ...