Multimedia Tools and Applications

Convolutional neural networks (CNNs) can learn the features of samples by supervised manner, and obtain outstanding achievements in many application fields. In order to improve the performance and generalization of CNNs, we propose a self-learning ...

Convolutional neural networks (CNNs) have achieved unprecedented competitiveness in text and two-dimensional image data processing because of its good accuracy performance and high detection speed. Graph convolutional networks (GCNs), as an ...

Vehicle re-identification (reID) often requires to recognize a target vehicle in large datasets captured from multi-cameras. It plays an important role in the automatic analysis of the increasing urban surveillance videos, which has become a hot ...

With the increasing amount of multimedia data, cross-modal retrieval has attracted more attentions in the area of multimedia and computer vision. To bridge the semantic gap between multi-modal data and improve the performance of retrieval, we ...

Pencil drawing is recognized as a typical non-photorealistic visual art form. It is attractive to automatically generate high-quality pencil drawings from real-world photographs. Traditional model-based methods are highlighted in their ...

Graph Convolutional Networks (GCNs) recently have been adopted in several feature representation studies for different classification tasks. While many of these methods are used to work with irregular structure data, they are rarely used to learn ...

Limited by the poor quality of the camera, transmission bandwidth, excessive compression and other factors, low-resolution images widely exist in our lives. Single image super-resolution method is a kind of image processing task which can obtain ...

Gait recognition from videos is a very important task for surveillance video analysis. Although a number of studies have explored gait recognition models, they lack clarity in the gait contour segmentation, which is an important but difficult step ...

Deep clustering obtains feature representation generally and then performs clustering for high dimension real-world data. However, conventional solutions are two-stage embedding learning-based methods and these two processes are separate and ...

The classification of images based on the principles of human vision is a major task in the field of computer vision. It is a common method to use multi-scale information and attention mechanism to obtain better classification performance. The ...

In order to improve the accuracy of CNN (convolutional neural network) in image classification, an enhanced Inception-ResNet-v2 model based on CNN is designed through the comparative study and analysis of the structure of classification model. ...

Video-text cross-modal retrieval is significant to computer vision. Most of existing works focus on exploring the global similarity between modalities, but ignore the influence of details on retrieval results. How to explore the correlation ...

Point cloud registration plays an important role in 3D computer vision. A challenge in this field is the presence of small salient objects with huge flat backgrounds in point clouds, which may result in poor registration. Despite substantial ...

Crowdsourcing learning (Bonald and Combes 2016; Dawid and Skene, J R Stat Soc: Series C (Appl Stat), 28(1):20–28 1979; Karger et al. 2011; Li et al, IEEE Trans Knowl Data Eng, 28(9):2296–2319 2016; Liu et al. 2012; Schlagwein and Bjorn-Andersen, J ...

In many advertising areas, banners are often generated with different display sizes, so designers have to make huge efforts to retarget their designs to each size. Automating such retargeting process can greatly save time for designers and let ...

Natural disasters are very unexpected in human life. The best prevention from such natural disasters is an early warning system which gives a good period to take some necessary measures during the occurrence of disasters. Social media is the best ...

In last decade, most of the multimedia IoT (M-IoT) applications are gaining popularity where the real-time still and streaming images are captured, and corresponding data is transported to cloud servers via communication networks. In such ...

The inherent scalability and flexibility of structured overlay networks makes them an excellent choice to support modern day applications with complex, volatile, mobile, and heterogeneous infrastructure. However, this heterogeneity and volatility ...

Cloud computing is a new technology that is increasing in popularity day-by-day. One of the reasons for its popularity can be its elasticity feature. In other words, cloud computing considers the consumer’s resource capacity to be infinite, where ...

People with hearing and speaking disabilities face significant hurdles in communication. The knowledge of sign language can help mitigate these hurdles, but most people without disabilities, including relatives, friends, and care providers, cannot ...

The Internet of Things (IoT) devices is being deployed in almost all aspects of human life starting from smart home, health monitoring, smart metering, to smart garbage collection and industrial applications. These devices sense and collects data ...

Structural Health Monitoring (SHM) of large structures is a critical aspect due to various environmental conditions, high speed & long-distance communication, dynamic analysis of the structure, and cost of operation. These issues can be addressed ...

Stock market is a dynamic and volatile market that is considered as time series data. The growth of financial data exposed the computational efficiency of the conventional systems. This paper proposed a hybrid deep learning model based on Long ...

Microblogs have become a customary news media source in recent times. But as synthetic text or ‘readfakes’ scale up the online disinformation operation, unsubstantiated pieces of information on social media platforms can cause significant havoc by ...

Various Human Activities are classified through time-series data generated by the sensors of wearable devices. Many real-time scenarios such as Healthcare Surveillance, Smart Cities and Intelligent surveillance etc. are based upon Human Activity ...$$$\mathrm{}$$$$\mathrm{}$

A burning challenge is balancing the demand for servers in computer data centers. In the modern era, the bulk of computer systems are used for big data and cloud computing. The Internet of Things (IoT) is becoming a hyper-world of physical, cyber ...

One of the major challenges in cyber space and Internet of things (IoT) environments is the existence of fake or phishing websites that steal users’ information. A website as a multimedia system provides access to different types of data such as ...

Nowadays, wireless sensor network (WSN) is an essential segment in the Internet of Things (IoT) paradigm. Essentially, WSN provides access to location, latest information of different objects of the environment, computing and communication for IoT ...