Shoulin Yin

• Doctor of Engineering
• PhD at Shenyang Normal University

INDEXED BY SCOPUS The International Conference on Advancements in Computational Intelligence for Knowledge Discovery & Diverse Applications (ICCIKDDA’2025) will focus on data assimilation, computation, and information processing, aiming to enhance the capabilities of computers as intelligent systems through the latest technological advancements acr...

Network security encompasses the strategies and techniques to protect networks from unauthorized access and potential threats. Network security is essential to protect layers of networks and data transferring on them. Data integrity and the underlying network infrastructure are necessary in today's digital landscape. This paper explores the role of...

Object detection is an important computer vision task, which is developed from image classification task. The difference is that it is no longer only to classify a single type of object in an image, but to complete the classification and positioning of multiple objects that may exist in an image at the same time. Classification refers to assigning...

Traditional semantic segmentation methods have problems such as poor multi-scale feature extraction ability, weak lightweight backbone network feature extraction ability, lack of effective fusion of context information, resulting in edge segmentation errors and feature discontinuity. In this paper, a novel semantic segmentation model based on multi...

The idea behind layered design is the foundation of the Internet of Things. Each tier uses a variety of technologies for capacity, preparation, and information transmission. With regard to the risks and vulnerabilities related to IoT-enabled devices, as well as potential assurance mechanisms in light of equipment constraints and novel information t...

Along with the computer application technology progress, machine learning, and block-chain techniques have been applied comprehensively in various fields. The application of machine learning, and block-chain techniques into medical image retrieval, classification and auxiliary diagnosis has become one of the research hotspots at present. Brain tumo...

The Internet of Things (IoT) is an advanced tech that transfers game data such as graphics, text, and other data over real-time networks. Game player surroundings can be sensed, or movement or situation can be observed for wearable devices that use sensors and actuators, this increases sales of wearables from 18 million in 2015 to 533.6 million uni...

The Internet of Multimedia Things, or IoMT, has grown significantly in the modern era. Major IoMT applications, like video surveillance and image processing, are used to monitor real-time settings in smart cities. A number of frameworks and techniques were put forth to improve IoT solutions. IoMT services must comply with user preferences and addre...

As computer vision algorithms have advanced rapidly, the widespread deployment of video surveillance systems has enhanced traffic safety and propelled the growth of intelligent highway systems. However, the intricate nature of real-world scenarios, particularly the presence of occlusions, introduces noise that can cause the loss of critical feature...

In recent years, driven by the continuous development of mobile Internet technology and artificial intelligence technology, the improvement of the manufacturing level of 6G Internet-of-Everything (IoE) products and the increase in residents’ income level, the 6G IoE industry has shown a sustained and stable development trend. However, 6G IoE has gr...

With the rapid development of computer hardware and big data processing technology, the bottleneck of intelligent analysis of massive data has changed from "how to deal with massive data quickly" to "how to mine valuable information quickly and effectively from massive data". Visualization and visualization analysis based on human visual perception...

https://www.routledge.com/Intelligent-Healthcare-Systems/Estrela/p/book/9781032052724 Medical cyber-physical systems, image processing, microscopy, security, biomedical imaging, multi-modal sensing, automation, robotics, network layers, software design, and biometrics for high computational load (CL) are shown. The book addresses the dimensionalit...

Virtual reality (VR) gaming (VRG) captures, examines, analysis, and renders the game data virtually instead of the users’ devices over efficient networks. E.g., VR is crucial in visually guided surgery and manifold therapies. Video Quality Assessment (VQA) helps VRG software and devices execute high-quality inputs/outputs. This paper debates VRG pr...

Nowadays, Blockchain is very popular among industries to solve security issues of information systems. The Internet of Things (IoT) has security issues during multi-organization communication, and any organization approves no such robust framework. The combination of blockchain technology with IoT makes it more secure and solves the problem of mult...

In the shadow detection task, the shadow model is usually consistent with the approximate contour of ontology semantics, it is difficult to extract the features of land covered objects or ground pixels, and easy to be confused into foreground objects in gray scale. Therefore, we present to formulate and apply one new threshold segmentation method b...

At present, the existing news recommendation system fails to fully consider the semantic information of news, meanwhile, the uneven popularity of news will also cause the phenomenon of long tail. Therefore, we propose a novel news recommendation model based on encoder graph neural network and Bat optimization in online social networks. Firstly, Bat...

Underwater image denoising technology is of great significance in underwater operation. Underwater operations (such as offshore oil drilling, undersea tunnels, pipeline construction, underwater archaeology, biological research, and lifesaving) require stable and clear underwater images to aid analysis. Due to the scattering and absorption of light...

With the development of deep learning technology, artificial intelligence has important applications in all aspects of society, but the lack of data has become a vital factor restricting the further evolution of artificial intelligence in industry 5.0. Federated learning can effectively use the edge node data and solve the data problem of artificia...

Pakistan views cyberspace as a critical source of power in the twenty-first century when governments no longer have complete control over power games. Private entities, terrorist groups, criminals, and people, on the other hand, are prominent players in cyberspace, offering unpredictable and multifaceted cyber risks to sensitive networks and infras...

The problems of data storage and sharing have been well solved with cloud storage. However, the disadvantage is that users' messages are stored in the cloud without encryption protection. Cloud storage managers can access or even obtain user data, which brings significant security risks to data owners. Therefore, some cloud storage centers adopt ci...

The book sheds light on medical cyber-physical systems while addressing image processing, microscopy, security, biomedical imaging, automation, robotics, network layers’ issues, software design, and biometrics, among other areas. Hence, solving the dimensionality conundrum caused by the necessity to balance data acquisition, image modalities, diffe...

Online education was widely launched worldwide with the increasing impact of Covid-19 and multiple online platforms were developed or improved due to their demands. Several surveys have been conducted to analyze the Covid-19 impact on education, revealing the importance of information and communication technology (ICT). This epidemic has significan...

Solutions to Intelligent Transportation Systems (ITS) can reduce fatalities enroute to hospitals while allowing health experts to serve people far away. Vehicular Ad Hoc Networks (VANETs) and Flying Ad Hoc Networks (FANETs) fit the bill, particularly in underdeveloped nations. Wireless Sensor Networks (WSNs) in healthcare are increasing, resulting...

Smart Healthcare System (SHS), whose functions contain the overall and highly connected coordinated operation, must rely on command centers, efficient transportation, healthcare staff, and receiving facilities. Integrated healthcare services, medical security, drug dispensing/supervision/follow-up, public health, and other services aiming to improv...

The DICOM medical imaging (MI) standard aids in sharing imageries across healthcare applications. The JPEG 2000 extends JPEG for therapeutic imaging relying on a Discrete Transformation along with wavelets. Nevertheless, JPEG 2000 is extremely unapt to encode certain visual arrangements and render good-quality 3D reconstruction. This paper analyzes...

Healthcare, as an elementary human entitlement, was not immune to new technology. The advancement of technology has made a substantial contribution to first-rate, on-time, acceptable, and cheap healthcare. Nanotechnology together with the Internet of Nanothings (IoNT) have consistently improved healthcare and significantly affected its evolution, r...

In today's healthcare, imaging is used for everything from diagnosis to surgery and follow-ups. Because most imaging modalities are digital, medical image processing must deal with massive data volumes and growing resolution. This text’s main themes are visual medical information and scalability to give effective and efficient responses to numerous...

Artificial Intelligence (AI) integrated with Blockchain distributed ledger technology (BDLT) has become the most attractive research area in the domain of renewable energy and related power automations. However, the increased use of renewable energy-enabled devices raised various challenging problems, such as smart grid-based control management, po...

The rapid growth of internet usage and its various applications , such as banking, shopping, social networks, and other business-related activities, has moved people closer to cyberspace. The implications of this growth have also come to Pakistan, where cyber security and threats are becoming an essential aspect of cyberspace. This paper will discu...

Federated learning can effectively ensure data security and improve the problem of data islanding. However, the performance of federated learning-based schemes could be better due to the imbalance of image data. Therefore, this paper proposes a federated learning approach based on priori knowledge and a bilateral segmentation network for image edge...

Nowadays, video streaming is very popular around the world, users use video streaming to watch online movies, education, and do office work. Video streaming is referred to as the transmission of video content, live or recorded from server/cloud to end-users. Video and music files are prearranged and transmitted in sequential packets of data so they...

Aiming at the existing problems of metric-based methods, there are problems such as inadequate feature extraction, inaccurate class feature representation, and single similarity measurement. A new model based on attention mechanism and weight fusion strategy is proposed in this paper. Firstly, the image is passed through the conv4 network with chan...

With the arrival of new data acquisition platforms derived from the Internet of Things (IoT), this paper goes beyond the understanding of traditional remote sensing technologies. Deep fusion of remote sensing and computer vision has hit the industrial world and makes it possible to apply Artificial intelligence to solve problems such as automatic e...

Remote sensing images contain important information such as airports, ports, and ships. By extracting remote sensing image features and learning the mapping relationship between image features and text semantic features, the interpretation and description of remote sensing image content can be realized, which has a wide range of application value i...

This paper proposes a novel remote sensing image segmentation method based on Gaussian mixture model and SURF algorithm. Firstly, Gaussian mixture model is used for remote sensing image segmentation. Then the surf matching algorithm is adopted for eliminating misidentified areas. The determinant of Hession matrix (DoH) is used to detect key points...

In space art design, the recognition of expression is of great help to the understanding of art. It is very difficult to obtain occlusion expression data from robot environment. In particular, it is very challenging to recognize the occluded expression. In the case of facial occlusion, it is difficult to extract the features of occluded expressions...

In order to realize fast and accurate search of sensitive regions in remote sensing images, we propose a multi-functional faster RCNN based on multi-scale feature fusion model for region search. The feature extraction network is based on ResNet50 and the dilated residual blocks are utilized for multi-layer and multi-scale feature fusion. We add a p...

Digital well-being records are multimodal and high-dimensional (HD). Better theradiagnostics stem from new computationally thorough and edgy technologies, i.e., hyperspectral (HSI) imaging, super-resolution, and nanoimaging, but advance mess data portrayal and retrieval. A patient's state involves multiple signals, medical imaging (MI) modalities,...

Nowadays, much research leverages the clustering to mine commercial patterns from data in enterprise systems. However, previous methods cannot fully consider local structures and global topology of data, which may cause the degradation of clustering performance. To address the challenges, a deep multimodal adversarial cycle-consistent network (DMAC...

Anatomical maps depicted by medical images reflect the health of the human body. Understanding the detailed division of the regions in the anatomical maps is helpful for diagnosis and further treatment. For example, the lung window contains the lung parenchyma, mediastinum, and diseased tumor. Accurate tumor segmentation can be more comprehensive a...

Remote sensing image object detection is widely used in civil and military fields. The important task is to detect objects such as ships, planes, airports, harbours and so on, and then it can obtain object category and position information. It is of great significance to use remote sensing images to observe the densely arranged and directional targ...

In the transmission of medical images, if the image is not processed, it is very likely to leak data and personal privacy, resulting in unpredictable consequences. Traditional encryption algorithms have limited ability to deal with complex data. e chaotic system is characterized by randomness and ergodicity, which has advantages over traditional en...

This paper presents a novel web-based crowdsourcing platform for the assessment of the subjective and objective quality of experience (QoE) of the video service in the cloud-server environment. The user has the option to enter subjective QoE data for video service by filling out a web questionnaire. The objective QoE data of the cloud-server, netwo...

For the massive large-scale visible image data obtained by satellite, unmanned aerial vehicles, and other reconnaissance platforms, if only relying on manual visual interpretation, there will be problems such as heavy workload, low efficiency, high repeatability, strong subjectivity, and high cost, which cannot meet the demand of modern society for...

Due to the large amount of image information data, high redundancy and high pixel correlation, the traditional medical image encryption algorithm is easy to be attacked by chosen plaintext. Therefore, a new medical image encryption algorithm combining genetic simulated annealing particle swarm optimization and modified quantum chaos system is propo...

Object detection in optical remote sensing imagery is being explored to deal with arbitrary orientations and complex appearance which is still a major issue in recent years. To perceive a better solution to the addressed problem, the post-processing of bounding boxes (BBs) has been evaluated and discussed for the applications of object detection. I...

Network intrusion can enter the network through informal channels. Some illegal users utilize Trojans and self-programmed attack to change the network security system, so that the system loses the defense and alarm function and the Hacker can steal the internal information. Network intrusion seriously harms the security of network information and t...

Presently, the stability and reproducibility of biomedical image detection are still deficient due to the instability and variability of biologically active units. These barriers will inevitably change with the rapid development of biology, informatics, medicine, materials science, and microelectronics. New expensive and hard-to-operate technologie...

According to the research works of the references on chaotic cryptanalysis, many recent chaotic image encryption algorithms cannot resist chosen-plaintext attacks. Although some chaotic image encryption algorithms introduce plain-image information, they still violate some design requirements of modern cryptosystems. The traditional image encryption...

With the rapid development of social network, intelligent terminal and automatic positioning technology, location-based social network (LBSN) service has become an important and valuable application. Point of interest (POI) recommendation is an important content in LBSN, which aims to recommend new locations of interest for users. It can not only a...

Behavior recognition is a research hotspot in the field of computer vision and it also is a challenging task. In particular, student behavior analysis has an impact on the efficiency of classroom education. Aiming at the complex student behavior recognition problem in the video, we propose a new feature fusion network for student behavior recogniti...

Network intrusion detection (NID) is an important method for network system administrators to detect various security holes. The performance of traditional NID methods can be affected when unknown or new attacks are detected. Compared with other machine learning methods, the intrusion detection method based on convolutional neural network (CNN) can...

The extensive acquisition and using of high-resolution remote sensing images have greatly promoted the development of airport detection. However, due to the complex shape, background and different scale of the airport location, the real-time and accuracy of airport detection are also facing major challenges. These factors can reduce the detection a...

Currently, medical image segmentation has attracted more attention from researchers, which can assist in medical diagnosis. However, in the process of traditional medical image segmentation, it is sensitive to the initial contour and noise, which is difficult to deal with the weak edge image, complex iterative process. In this paper, we propose a n...

Traditional object detection algorithms and strategies are difficult to meet the requirements of data processing efficiency, performance, speed and intelligence in object detection. Through the study and imitation of the cognitive ability of the brain, deep learning can analyze and process the data features. It has a strong ability of visualization...

Airport detection in remote sensing images is an important process which plays a significant role in military and civil areas. Mostly, conventional algorithms have been used for airport detection from a small-scale remote sensing image and revealed the less efficient ability of searching the object from a large-scale high-resolution remote sensing...

To address the low accuracy problem of playground detection under complex background, the accurate playground localization based on multi-feature extraction and cascade classifier is proposed in this paper. It is difficult to utilize this information to separate objects from the complex background. Therefore, we adopt multi-feature extraction metho...

Medical data have the characteristics of particularity and complexity. Big data clustering plays a significant role in the area of medicine. The traditional clustering algorithms are easily falling into local extreme value. It will generate clustering deviation, and the clustering effect is poor. Therefore, we propose a new medical big data cluster...

Hot region selection (HRS) is usually performed for larger scenes, especially in military target detection and battlefield situational awareness applications. Many state-of-the-art methods pay more attention on object detection. Although they can detect the region of interest in one image, these images are highly affected by illumination, rotation,...

Currently, gesture recognition provides a faster, simpler, convenient, effective and more natural way for human-computer interaction, which has been widely concerned. Gesture recognition plays an important role in real life. The manual feature extraction in traditional gesture recognition methods is time-consuming and strenuous. Moreover, in order...

Medical image segmentation is one of the hot issues in the related area of image processing. Precise segmentation for medical images is a vital guarantee for follow-up treatment. At present, however, low gray contrast and blurred tissue boundaries are common in medical images, and the segmentation accuracy of medical images cannot be effectively im...

As the continuous development of mobile social network, the structure of mobile social network increasingly becomes complex. It not only speeds up the information transmission between people, but also expands the scope of information exchange, which has become an essential and important social media in people’s social life. How to effectively ident...

Nowadays, Internet of things not only brings promising opportunities but also faces a lot of challenges. It attracts a lot of researchers’ attention and has important economic and social values. Internet of things plays a key role in the big data processing, especially in image field. Image de-noising still is a key problem in image pre-processing....

Currently, big data is a new and hot issue. Particularly, the rapid growth of the Internet of Things causes a sharp growth of data. Enormous amounts of networking sensors are continuously collecting and transmitting data to be stored and processed in the cloud, including remote sensing data, environmental data, and geographical data. And region is...

Traditional image segment algorithms have some demerits: edge blur, discontinuous edge is susceptible to peripheral irrelevant information, Poor noise resistance. Therefore, we propose an improved krill group-based region growing algorithm for image segmentation in this paper. First, texture feature of the image is extracted by using Gabor filter....

User interface (UI) is an interaction and information exchange medium between systems and users, which is convenient to communicate and enable users to operate hardware easily and effectively to achieve the bidirectional interaction. Traditional UI has difficulty in satisfying requirements of users. Therefore, this paper proposes a new intelligence...

Though many intelligence algorithms are used for travelling salesman problem (TSP), the main objective of this paper is to execute new approach to obtain significant improvements. This paper proposes an improved Wolf colony search algorithm based on search strategy. First, we introduce interaction strategy into travel behaviour and calling behaviou...

Currently, image de-noising has become a hot topic for image classical solution of the estimation problem. The effectiveness of wavelet-based threshold functions for image de-noising is taken into consideration. Therefore, many wavelet threshold functions are proposed to improve the effectiveness of image de-noising, such as hard?threshold, soft th...

Recent research progress in shadow detection has leveraged the development of remote sensing and computer vision. Since shadows of buildings, trees, bridges in one image can provide useful information about the scene to help people understand the shape, feature or estimate their locations and orientations of original objects, especially for damaged...

Automatic Chinese word segmentation is a hot issue in information extraction, machine translation, information retrieval, automatic text categorization, speech recognition, and the voice conversion, natural language understanding. English uses a space as a nature delimiter, but because Chinese inherits from the ancient Chinese tradition, there is n...

Image fusion is an important part of image processing because it can collaboratively use image information from different sensors for the same scene. Image fusion outputs the images, which are more suitable for human visual perception or computer processing and analysis; furthermore, it can obviously improve the shortcomings of a single sensor, as...

Scene complexity has a great effect on road feature extraction, such as shadow and obstructions. In order to extract high-precision road feature, we propose a new support vector machine (SVM) based on krill herb algorithm used for a fast road feature extraction. This new scheme includes three steps. First, image is smoothed and we use fuzzy c-means...

With the ever-increasing amount and complexity of remote sensing image data, the development of large-scale image segmentation analysis algorithms has not kept pace with the need for methods that improve the final accuracy of object recognition. In particular, the development of such methods for large scale images poses a considerable challenge. Tr...

To alleviate the disadvantage of traditional image denoising method in big images data, we propose a modified pyramid dual tree direction filter with nonlocal mean multigrade remnant filter for image denoising in this paper. The proposed denoising method is partitioned into 4 processes. Firstly, curvature scale model is used for building pyramid du...

In this paper, we propose a novel method based on discrete firefly algorithm for traveling salesman problem. We redefine the distance of firefly algorithm by introducing swap operator and swap sequence to avoid algorithm easily falling into local solution and accelerate convergence speed. In addition, we adopt dynamic mechanism based on neighborhoo...

Data stream sliding window is a common query method, but traditional approaches can get inaccurate data results. Due to the blocked character of join and the infinite character of data stream, there must be some constraints on join operations. In order to solve these constraints, this paper proposes a strategy based on load shedding techniques for...

The original BP neural network has some disadvantages, such as slow convergence speed, low precision, which is easy to fall into local minimum value. So this paper proposes an improved particle swarm optimization (PSO) algorithm to optimize BP neural network. In this new algorithm, PSO uses improved adaptive acceleration factor and improved adaptiv...