Cloud‐based video streaming services: Trends, challenges, and opportunities
- Tajinder Kumar,
- Purushottam Sharma,
- Jaswinder Tanwar,
- Hisham Alsghier,
- Shashi Bhushan,
- Hesham Alhumyani,
- Vivek Sharma,
- Ahmed I. Alutaibi
Cloud computing has drastically changed the delivery and consumption of live streaming content. The designs, challenges, and possible uses of cloud computing for live streaming are studied. A comprehensive overview of the technical and business ...
Machine learning and human‐machine trust in healthcare: A systematic survey
As human‐machine interaction (HMI) in healthcare continues to evolve, the issue of trust in HMI in healthcare has been raised and explored. It is critical for the development and safety of healthcare that humans have proper trust in medical ...
Learning feature alignment and dual correlation for few‐shot image classification
Few‐shot image classification is the task of classifying novel classes using extremely limited labelled samples. To perform classification using the limited samples, one solution is to learn the feature alignment (FA) information between the ...
Mixed‐decomposed convolutional network: A lightweight yet efficient convolutional neural network for ocular disease recognition
Eye health has become a global health concern and attracted broad attention. Over the years, researchers have proposed many state‐of‐the‐art convolutional neural networks (CNNs) to assist ophthalmologists in diagnosing ocular diseases ...
Rule acquisition of three‐way semi‐concept lattices in formal decision context
Three‐way concept analysis is an important tool for information processing, and rule acquisition is one of the research hotspots of three‐way concept analysis. However, compared with three‐way concept lattices, three‐way semi‐concept lattices ...
3D reconstruction and defect pattern recognition of bonding wire based on stereo vision
Non‐destructive detection of wire bonding defects in integrated circuits (IC) is critical for ensuring product quality after packaging. Image‐processing‐based methods do not provide a detailed evaluation of the three‐dimensional defects of the ...
Car‐following strategy of intelligent connected vehicle using extended disturbance observer adjusted by reinforcement learning
Disturbance observer‐based control method has achieved good results in the car‐following scenario of intelligent and connected vehicle (ICV). However, the gain of conventional extended disturbance observer (EDO)‐based control method is usually ...
Multi‐scale cross‐domain alignment for person image generation
Person image generation aims to generate images that maintain the original human appearance in different target poses. Recent works have revealed that the critical element in achieving this task is the alignment of appearance domain and pose ...
A verifiable essential secret image sharing scheme based on HLRs (VESIS‐(t, s, k, n))
In traditional secret image sharing schemes, a secret image is shared among shareholders who have the same position. But if the shareholders have two different positions, essential and non‐essential, it is necessary to use essential secret image ...
An object detection approach with residual feature fusion and second‐order term attention mechanism
Automatically detecting and locating remote occlusion small objects from the images of complex traffic environments is a valuable and challenging research. Since the boundary box location is not sufficiently accurate and it is difficult to ...
Deep reinforcement learning using least‐squares truncated temporal‐difference
Policy evaluation (PE) is a critical sub‐problem in reinforcement learning, which estimates the value function for a given policy and can be used for policy improvement. However, there still exist some limitations in current PE methods, such as ...
Attention‐based network embedding with higher‐order weights and node attributes
Network embedding aspires to learn a low‐dimensional vector of each node in networks, which can apply to diverse data mining tasks. In real‐life, many networks include rich attributes and temporal information. However, most existing embedding ...
Generative adversarial networks based motion learning towards robotic calligraphy synthesis
Robot calligraphy visually reflects the motion capability of robotic manipulators. While traditional researches mainly focus on image generation and the writing of simple calligraphic strokes or characters, this article presents a generative ...
Geometric prior guided hybrid deep neural network for facial beauty analysis
Facial beauty analysis is an important topic in human society. It may be used as a guidance for face beautification applications such as cosmetic surgery. Deep neural networks (DNNs) have recently been adopted for facial beauty analysis and have ...
Two kinds of average approximation accuracy
Rough set theory places great importance on approximation accuracy, which is used to gauge how well a rough set model describes a target concept. However, traditional approximation accuracy has limitations since it varies with changes in the ...
A multi‐feature‐based intelligent redundancy elimination scheme for cloud‐assisted health systems
Redundancy elimination techniques are extensively investigated to reduce storage overheads for cloud‐assisted health systems. Deduplication eliminates the redundancy of duplicate blocks by storing one physical instance referenced by multiple ...
An artificial systems, computational experiments and parallel execution‐based surface electromyogram‐driven anti‐disturbance zeroing neurodynamic strategy for upper limb human‐robot interaction control
In recent years, intelligent robots are extensively applied in the field of the industry and intelligent rehabilitation, wherein the human‐robot interaction (HRI) control strategy is a momentous part that needs to be ameliorated. Specially, the ...
A versatile humanoid robot platform for dexterous manipulation and human–robot collaboration
Humanoid robots have attracted much attention by virtue of their compatibility with human environments. However, biped humanoids with immense promise still cannot function steadily and reliably in real‐world settings in the current state. Hence, ...
