Shuai Liu

Hunan Normal University · School of Educational Sciences

Today, new generation of artificial intelligence has brought several new research domains such as computer vision (CV).Thus, target tracking, the base of CV, has been a hotspot research domain. Correlation filter (CF) based algorithm has been the base of real-time tracking algorithms because of thehigh tracking efficiency, however, CF based algorit...

In the era of rapid development of artificial intelligence, the integration of multimedia and human-artificial intelligence (H-AI) has become an important research hotspot. Especially in the multimedia environment, effective remote visual monitoring has become the exploration direction of many scholars. The use of traditional filtering algorithm (C...

With the rapid development of Artificial Intelligence (AI), deep learning has increasingly become a research hotspot in various fields, such as medical image classification. Traditional deep learning models use Bilinear Interpolation when processing classification tasks of multi-size medical image dataset, which will cause the loss of information o...

In the Industry 4.0 era, the visualization and real-time automatic monitoring of smart cities supported by the Internet of Things is becoming increasingly important. The use of filtering algorithms in smart city monitoring is a feasible method for this purpose. However, maintaining fast and accurate monitoring in complex surveillance environments w...

Computer vision has always been a hot field of research by contemporary scholars due to its wide range of applications. As an important branch of this field, visual monitoring technology has shown superior vitality in the actual monitoring environment of the Internet of Things (IoT). However, when the monitoring environment is complex, once the tar...

As an important part of core competencies in the 21 st century, computational thinking has received a lot of attention from all over the world. In the field of higher education, cultivating the ability of computational thinking has become an important goal of teaching. Previous research has shown that students' learning engagement is related to par...

Temporal action localisation is a key research direction for video understanding in the field of computer vision. Current methods of using an attention mechanism only divides the video frame into an action instance frame and a background frame. As a result, the action context, which should belong to the background is misclassified into an action in...

The global outbreak of COVID-19 has become an important research topic in healthcare since 2019. RT-PCR is the main method for detecting COVID-19, but the long detection time is a problem. Therefore, the pathological study of COVID-19 with CT image is an important supplement to RT-RCT. The current TVLoss-based segmentation promotes the connectivity...

In the era of rapid development of artificial intelligence, the integration of multimedia and human-artificial intelligence (H-AI) has become an important research hotspot. Especially in the multimedia environment, effective remote visual monitoring has become the exploration direction of many scholars. The use of traditional filtering algorithm (C...

The ability of independent innovation in the field of artificial intelligence is a key element to occupy the commanding heights of future technology and talent competition in China. The cultivation of artificial intelligence talents, especially the cultivation high-end talent, it is essential to promote the development of artificial intelligence in...

China’s independent innovation ability in the field of artificial intelligence is a key link to occupy the commanding heights of future science and technology and talent competition. The cultivation of artificial intelligent talents is crucial to promote the development of the artificial intelligent industry. There is a large demand for artificial...

The segmentation of glioma by computer vision is one of the hot topics in medical image analysis, which further helps doctors to make a better treatment plan for glioma. At present, convolutional neural networks (CNN) with multi-kernels are the mainstream method to identify glioma regions. However, the segmentation is strongly affected if the inten...

In recent years, deep learning has revolutionized computer vision and has been widely used for monitoring in diverse visual scenes. However, in terms of some aspects such as complexity and explainability, deep learning is not always preferable over traditional machine-learning methods. Traditional visual tracking approaches have shown certain advan...

Occlusion, rotation and other factors affect human motion structure because of the incomplete acquired image sequence, resulting in poor performance of non-rigid three-dimensional (3D) motion pose reconstruction. A non-rigid 3D reconstruction and high-precision correction method for motion pose are studied in this paper. A non-rigid imaging model i...

Remote monitoring is an important application of intelligent transportation systems (ITSs). The combination of monitoring equipment and tracking algorithms can be used to automatically track moving targets. The tracking algorithm based on the Siamese network is both accurate and efficient, and its development potential is better than that of other...

The global outbreak of COVID-19 has become an important research topic in healthcare since 2019. RT-PCR is the main method for detecting COVID-19, but the long detection time is a problem. Therefore, the pathological study of COVID-19 with CT image is an important supplement to RT-RCT. The current TVLoss based segmentation promotes the connectivity...

Automated diagnostic techniques based on computed tomography (CT) scans of the chest for the coronavirus disease (COVID-19) help physicians detect suspected cases rapidly and precisely, which is critical in providing timely medical treatment and preventing the spread of epidemic outbreaks. Existing capsule networks have played a significant role in...

Multimodal emotion recognition, that is, emotion recognition uses machine learning to generate multi-modal features on the basis of videos which has become a research hotspot in the field of artificial intelligence. Traditional multi-modal emotion recognition method only simply connects multiple modalities, and the interactive utilization rate of m...

In the period of rapid development on the new information technologies, computer vision has become the most common application of artificial intelligence, which is represented by deep learning in the current society. As the most direct and effective application of computer vision, facial expression recognition (FER) has become a hot topic and used...

Action recognition in video is a research hot spot in the field of computer vision. Learning important clues in video context has significant effect to promote the interaction prediction and gesture recognition. Most existing methods infer the interactions between actor and context through relational reasoning methods. While these relational featur...

Today, target detection has an indispensable application in various fields. Infrared small-target detection, as a branch of target detection, can improve the perception capability of autonomous systems, and it has good application prospects in infrared alarm, automatic driving and other fields. There are many well-established algorithms that perfor...

The accuracy of WiFi fingerprint-based localization is related to the number of reference points, generally, to obtain better positioning accuracy, enough samples must be collected, which will inevitably lead to a huge sampling workload. Thus, it will be of great significance to design an algorithm using sparse samples to achieve positioning accura...

Background The new global pandemic caused by the 2019 novel coronavirus (COVID-19), novel coronavirus pneumonia, has spread rapidly around the world, causing enormous damage to daily life, public health security, and the global economy. Early detection and treatment of COVID-19 infected patients are critical to prevent the further spread of the epi...

Chromosome images are commonly used in karyotype analysis to diagnose chromosomal diseases. However, there are often chromosome adhesion and overlaps in chromosome images, so effective chromosome segmentation is conducive to smooth karyotype analysis. To date, some progress has been made in automatic chromosome segmentation, and existing methods ca...

Prenatal karyotype diagnosis is important to determine if the foetus has genetic diseases and some congenital diseases. Chromosome classification is an important part of karyotype analysis, and the task is tedious and lengthy. Chromosome classification methods based on deep learning have achieved good results, but if the quality of the chromosome i...

From early 2020, a novel coronavirus disease pneumonia has shown a global “pandemic” trend at an extremely fast speed. Due to the magnitude of its harm, it has become a major global public health event. In the face of dramatic increase in the number of patients with COVID-19, the need for quick diagnosis of suspected cases has become particularly c...

In healthcare, the human body is a controlled input-output system, which generates different observations with the variations of external interventions. The intervention acts as the input, and the output is the phenotype observation that reflects the latent health state of the body system. The objective of healthcare is to determine effective inter...

Reliability is an important property in the applied engineering systems, especially in visual tracking. The supervised visual tracking method uses reliable ground truth that is manually annotated, which is hard to get in many applications. However, weakly supervised visual trackings are limited by the low-quality labels. Therefore, a reliable sampl...

In the process of wireless image transmission, there are a large number of interference signals, but the traditional interference signal recognition system is limited by various modulation modes, it is difficult to accurately identify the target signal, and the reliability of the system needs to be further improved. In order to solve this problem,...

With the continuous improvement of human living standards, dietary habits are constantly changing, which brings various bowel problems. Among them, the morbidity and mortality rates of colorectal cancer have maintained a significant upward trend. In recent years, the application of deep learning in the medical field has become increasingly spread a...

In the field of real-time image enhancement, image super-resolution (SR) is an important research hotspot. As an image super-resolution method, deep learning can extract more stable and higher level features. However, image super-resolution processing is an ill posed problem. Due to the lack of self-attentional negative feedback mechanism, the exis...

Target enhancement is the most important task in a video surveillance system. In order to improve the accuracy and efficiency of target enhancement, and better deal with the subsequent recognition, tracking, behaviour understanding and other processing of targets, a deep learning-based image enhancement algorithm for video surveillance scenes is pr...

With the rapid development in computer vision domain, research on object tracking has directed more attention by scholars. Out of view (OV) is an important challenge often encountered in the tracking process of objects, especially in Internet of Things surveillance. Therefore, this paper proposes a fuzzy-aided solution for OV challenge. This soluti...

As an emerging biomedical image processing technology, medical image segmentation has made great contributions to sustainable medical care. Now it has become an important research direction in the field of computer vision. With the rapid development of deep learning, medical image processing based on deep convolutional neural networks has become a...

The meminductor is a new type of memory circuit element which is defined based on the memristor. To explore the application of the meminductor in the nonlinear circuits, a mathematical model of meminductor is proposed and applied to nonlinear circuits. In this work, a simple meminductor-based chaotic system is designed. The equilibrium point of the...

Chinese word segmentation is an important research direction in related research on elementary mathematics knowledge extraction. The speed of segmentation directly affects subsequent applications, and the accuracy of segmentation directly affects corresponding research in the next step. In the machine learning methods for extracting basic mathemati...

This two-volume set constitutes the post-conference proceedings of the 4th EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2020, held in Binzhou, China, in September 2020. Due to COVID-19 the conference was held virtually. The 89 papers presented were selected from 190 submissions and focus on theory and application of...

This two-volume set constitutes the post-conference proceedings of the 4th EAI International Conference on Advanced Hybrid Information Processing, ADHIP 2020, held in Binzhou, China, in September 2020. Due to COVID-19 the conference was held virtually. The 89 papers presented were selected from 190 submissions and focus on theory and application of...

This 2-volume set constitutes the proceedings of the 7th International Conference on e-Learning, e-Education, and Online Training, eLEOT 2021, held in Xinxiang, China, in June 2021. The 104 full papers presented were carefully reviewed and selected from 218 submissions. The papers are structured into two subject areas: New Trends of Teaching: Evalu...

This 2-volume set constitutes the proceedings of the 7th International Conference on e-Learning, e-Education, and Online Training, eLEOT 2021, held in Xinxiang, China, in June 2021. The 104 full papers presented were carefully reviewed and selected from 218 submissions. The papers are structured into two subject areas: New Trends of Teaching: Evalu...

Today, artificial intelligence is everywhere in people's daily lives. Visual tracking, which is used to identify and continuously track specific targets, is an important research domain in the study of artificial intelligence. However, current visual tracking methods are not accurate enough for object tracking with background clutter, which can eas...

The increment of communication technologies and the development of signal processing require efficient identification techniques for communication radiation. However, the complex characteristics of electromagnetic environment are not adequately handled by linear methods. Since the fractal theory is well suited for nonlinear problems, the relation o...

Data storage, especially big data storage, is a research hot spot in Internet of Things (IoT) system today. In traditional data storage methods, the fault-tolerant algorithm for data copies is adjusted with whole data file, which causes huge redundancy because there are less utilization and more cost of data storage when only a part of data blocks...

An important area of computer vision is real-time object tracking, which is now widely used in intelligent transportation and smart industry technologies. Although the correlation filter object tracking methods have a good real-time tracking effect, it still faces many challenges such as scale variation, occlusion, and boundary effects. Many schola...

Reliability has been widely used in industrial IoT (IIoT) applications. Since maintaining fast and accurate tracking of targets with fast move and motion blur in industrial applications is still a major challenge, this paper proposes a novel mechanism based on reliability for target matching, which is the basic problem in computer vision. Then, by...

Mining useful patterns from databases is an important research topic. The research in utility mining mostly focuses on discovering patterns of high value in large databases, and analyzing the important factors in a data mining process. This idea is applied to the wireless device identification in this paper. Radio Frequency Fingerprint (RFF) reflec...

Deciphering the dynamic changes of core factors at different reprogramming stages plays an important role in elucidating the reprogramming mechanism of induced pluripotent stem cells (iPSCs) and improving their induction efficiency. The use of transcription factors (TFs) in combination with histone modification is vital to understand the multiple r...

(Aim) Currently, there are many methods to identify sensorineural hearing loss via magnetic resonance imaging. This study aims to develop a more efficient approach. (Methods) Our approach used discrete wavelet packet entropy as the feature-extraction method. It used single-hidden layer feedforward neural network as the classifier model. A bio-inspi...

This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. The...

This two-volume book constitutes the refereed proceedings of the Second International Conference on Multimedia Technology and Enhanced Learning, ICMTEL 2020, held in Leicester, United Kingdom, in April 2020. Due to the COVID-19 pandemic all papers were presented in YouTubeLive. The 83 revised full papers have been selected from 158 submissions. The...

This 2-volume set constitutes the proceedings of the 6th International Conference on e-Learning, e-Education, and Online Training, eLEOT 2020, held in Changsha, China, in June 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 full papers presented were carefully reviewed and selected from 141 submissions. They focus on mo...

This 2-volume set constitutes the proceedings of the 6th International Conference on e-Learning, e-Education, and Online Training, eLEOT 2020, held in Changsha, China, in June 2020. The conference was held virtually due to the COVID-19 pandemic. The 68 full papers presented were carefully reviewed and selected from 141 submissions. They focus on mo...

When detecting micro-distortion of lidar scanning signals, current hardwires and algorithms have low compatibility, resulting in slow detection speed, high energy consumption, and poor performance against interference. A geometric statistics-based micro-distortion detection technology for lidar scanning signals was proposed. The proposed method bui...

Current accounting methods for small and medium-sized enterprises (SMEs) have long running times and low user satisfaction. Therefore, a method for the selection of accounting models for SMEs based on accounting market big data (AMBD) is proposed in this paper. Firstly, some indicators such as the current ratio, quick ratio, asset-liability ratio,...

Nucleosome positioning played significant roles in various biological processes. With the development of high-throughput techniques, many methods and software were developed for nucleosome positioning. Although results with high accuracy (Acc) were obtained, the key factors for determining nucleosome positioning under less time complexity remain un...

As one of the leading killers of females, breast cancer has become one of the heated research topics in the community of clinical medical science and computer science. In the clinic, mammography is a publicly accepted technique to detect early abnormalities such as masses and distortions in breast leading to cancer. Interpreting the images, however...

In social network big data scheduling, it is easy for target data to conflict in the same data node. Of the different kinds of entropy measures, this paper focuses on the optimization of target entropy. Therefore, this paper presents an optimized method for the scheduling of big data in social networks and also takes into account each task’s amount...

Unsupervised feature selection (UFS) as an effective method to reduce time complexity and storage burden has been widely applied to various machine learning tasks. The selected features should model data distribution, preserve data reconstruction and maintain manifold structure. However, most UFS methods don’t consider these three factors simultane...

Understanding the target regulation between pioneer factor and its binding genes is crucial for improving the efficiency of TF-mediated reprogramming. Oct4 as the only one factor that cannot be substituted by other POU members, it is urgent need to develop a quantitative model for describing the spatial binding pattern with its target genes. The dy...