Open Access

ARTICLE

Journal on Artificial Intelligence, Vol.6, pp. 1-21, 2024, DOI:10.32604/jai.2024.047226
Abstract With the increased accessibility of global trade information, transaction fraud has become a major worry in global banking and commerce security. The incidence and magnitude of transaction fraud are increasing daily, resulting in significant financial losses for both customers and financial professionals. With improvements in data mining and machine learning in computer science, the capacity to detect transaction fraud is becoming increasingly attainable. The primary goal of this research is to undertake a comparative examination of cutting-edge machine-learning algorithms developed to detect credit card fraud. The research looks at the efficacy of these machine learning algorithms using a publicly available… More >

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Journal on Artificial Intelligence, Vol.6, pp. 23-42, 2024, DOI:10.32604/jai.2023.045617
Abstract Movies reviews provide valuable insights that can help people decide which movies are worth watching and avoid wasting their time on movies they will not enjoy. Movie reviews may contain spoilers or reveal significant plot details, which can reduce the enjoyment of the movie for those who have not watched it yet. Additionally, the abundance of reviews may make it difficult for people to read them all at once, classifying all of the movie reviews will help in making this decision without wasting time reading them all. Opinion mining, also called sentiment analysis, is the process of identifying and extracting… More >

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Journal on Artificial Intelligence, Vol.6, pp. 43-52, 2024, DOI:10.32604/jai.2024.047642
Abstract This article presents a real-time localization method for Unmanned Aerial Vehicles (UAVs) based on continuous image processing. The proposed method employs the Scale Invariant Feature Transform (SIFT) algorithm to identify key points in multi-scale space and generate descriptor vectors to match identical objects across multiple images. These corresponding points in the image provide pixel positions, which can be combined with transformation equations, allow for the calculation of the UAV’s actual ground position. Additionally, the physical coordinates of matching points in the image can be obtained, corresponding to the UAV’s physical coordinates. The method achieves real-time positioning and tracking during UAV… More >

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68

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Journal on Artificial Intelligence, Vol.6, pp. 53-69, 2024, DOI:10.32604/jai.2024.049083
Abstract In multi-label learning, the label-specific features learning framework can effectively solve the dimensional catastrophe problem brought by high-dimensional data. The classification performance and robustness of the model are effectively improved. Most existing label-specific features learning utilizes the cosine similarity method to measure label correlation. It is well known that the correlation between labels is asymmetric. However, existing label-specific features learning only considers the private features of labels in classification and does not take into account the common features of labels. Based on this, this paper proposes a Causality-driven Common and Label-specific Features Learning, named CCSF algorithm. Firstly, the causal learning… More >

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Journal on Artificial Intelligence, Vol.6, pp. 71-83, 2024, DOI:10.32604/jai.2024.045332
Abstract One of the significant issues the insurance industry faces is its ability to predict future claims related to individual policyholders. As risk varies from one policyholder to another, the industry has faced the challenge of using various risk factors to accurately predict the likelihood of claims by policyholders using historical data. Traditional machine-learning models that use neural networks are recognized as exceptional algorithms with predictive capabilities. This study aims to develop a deep learning model using sequential deep regression techniques for insurance claim prediction using historical data obtained from Kaggle with 1339 cases and eight variables. This study adopted a… More >

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REVIEW

Journal on Artificial Intelligence, Vol.4, No.2, pp. 99-114, 2022, DOI:10.32604/jai.2022.031235
Abstract The process of segmenting point cloud data into several homogeneous areas with points in the same region having the same attributes is known as 3D segmentation. Segmentation is challenging with point cloud data due to substantial redundancy, fluctuating sample density and lack of apparent organization. The research area has a wide range of robotics applications, including intelligent vehicles, autonomous mapping and navigation. A number of researchers have introduced various methodologies and algorithms. Deep learning has been successfully used to a spectrum of 2D vision domains as a prevailing A.I. methods. However, due to the specific problems of processing point clouds… More >

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Journal on Artificial Intelligence, Vol.4, No.1, pp. 1-13, 2022, DOI:10.32604/jai.2022.028092
Abstract Leukemia is the cancer that starts in the blood cells due to the excess production of immature leucocytes that replace the cells with normal blood cells. Physicians rely on their experience to determine the type and subtype of Leukemia from the blood sample. Most people are misdiagnosed when it comes to its subtypes, the error rates can be up to 40% during the classification process. That too depends on the expertise of the physician. This research represents a Convolutional Neural Network based medical image classifier. The proposed technique can classify Leukemia and its five subtypes. State of the art deep… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.4, No.2, pp. 61-76, 2022, DOI:10.32604/jai.2022.028140
Abstract Today, more families are affected by Diabetes Mellitus (DM) disease on account of its continually increasing occurrence. Most patients remain unknown about their health quality or the DM’s risk factors prior to diagnosis. The medical world has witnessed that individuals are affected by two different diabetes namely a) Type-1 diabetes (T1D), as well as b) Type-2 diabetes (T2D). As Type 2 Diabetes affects the other organs of the body, the proposed system concentrates specifically on Type 2 Diabetes. This work aims to ascertain the cardiac disorder in T2D patients. As of the ECG dataset, the requisite data is gathered it… More >

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983

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Journal on Artificial Intelligence, Vol.4, No.1, pp. 37-48, 2022, DOI:10.32604/jai.2022.027875
Abstract Deep kernel mapping support vector machines have achieved good results in numerous tasks by mapping features from a low-dimensional space to a high-dimensional space and then using support vector machines for classification. However, the depth kernel mapping support vector machine does not take into account the connection of different dimensional spaces and increases the model parameters. To further improve the recognition capability of deep kernel mapping support vector machines while reducing the number of model parameters, this paper proposes a framework of Lightweight Deep Convolutional Cross-Connected Kernel Mapping Support Vector Machines (LC-CKMSVM). The framework consists of a feature extraction module… More >

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671

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ARTICLE

Journal on Artificial Intelligence, Vol.4, No.1, pp. 27-35, 2022, DOI:10.32604/jai.2022.027839
Abstract Deep deterministic policy gradient (DDPG) has been proved to be effective in optimizing particle swarm optimization (PSO), but whether DDPG can optimize multi-objective discrete particle swarm optimization (MODPSO) remains to be determined. The present work aims to probe into this topic. Experiments showed that the DDPG can not only quickly improve the convergence speed of MODPSO, but also overcome the problem of local optimal solution that MODPSO may suffer. The research findings are of great significance for the theoretical research and application of MODPSO. More >

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Journal on Artificial Intelligence, Vol.4, No.2, pp. 115-132, 2022, DOI:10.32604/jai.2022.030353
Abstract The rapid development of information technologies such as artificial intelligence, Internet and big data has promoted the deep integration of technology and education, especially the rise of large-scale online courses, which provides a great opportunity for curriculum teaching reform in colleges and universities. At the same time, artificial intelligence, as a cutting-edge technology, has good development prospects and has become a popular professional course in colleges and universities, artificial intelligence technology has become the focus of subject education in many universities. The combination of online education and AI courses will also greatly enhance the enthusiasm of users and expand the… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.4, No.3, pp. 133-142, 2022, DOI:10.32604/jai.2022.031800
Abstract How to quickly and accurately identify applications in VPN encrypted tunnels is a difficult technique. Traditional technologies such as DPI can no longer identify applications in VPN encrypted tunnel. Various VPN protocols make the feature engineering of machine learning extremely difficult. Deep learning has the advantages that feature extraction does not rely on manual labor and has a good early application in classification. This article uses deep learning technology to classify the applications of VPN encryption tunnel based on the SAE-2dCNN model. SAE can effectively reduce the dimensionality of the data, which not only improves the training efficiency of 2dCNN,… More >

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590

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ARTICLE

Journal on Artificial Intelligence, Vol.4, No.2, pp. 77-84, 2022, DOI:10.32604/jai.2022.028511
Abstract According to the current problems of higher education management informatization, this paper puts forward a development scheme of collaborative platform on education management. The main technology includes three parts. First, integrate the distributed database and use two-tier linked list to realize dynamic data access. Second, the relation graph is used to display the data of each student, so as to realize the visual sharing of data. Third, realize the collaborative information security mechanism from three aspects to ensure the legal sharing of data. Finally, the platform development is completed with Java. It can help to improve the effectiveness of educating… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.4, No.1, pp. 49-60, 2022, DOI:10.32604/jai.2022.017992
Abstract Huge amount of data is being produced every second for microblogs, different content sharing sites, and social networking. Sentimental classification is a tool that is frequently used to identify underlying opinions and sentiments present in the text and classifying them. It is widely used for social media platforms to find user's sentiments about a particular topic or product. Capturing, assembling, and analyzing sentiments has been challenge for researchers. To handle these challenges, we present a comparative sentiment analysis study in which we used the fine-grained Stanford Sentiment Treebank (SST) dataset, based on 215,154 exclusive texts of different lengths that are… More >

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583

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ARTICLE

Journal on Artificial Intelligence, Vol.4, No.2, pp. 85-98, 2022, DOI:10.32604/jai.2022.029141
Abstract Sorting the Tibetan language quickly and accurately requires first identifying the component elements that make up Tibetan syllables and then sorting by the priority of the component. Based on the study of Tibetan text structure, grammatical rules and syllable structure, we present a structure-based Tibetan syllable recognition method that uses syllable structure instead of grammar. This method avoids complicated Tibetan grammar and recognizes the components of Tibetan syllables simply and quickly. On the basis of identifying the components of Tibetan syllables, a Tibetan syllable sorting algorithm that conforms to the language sorting rules is proposed. The core of the Tibetan… More >

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619

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ARTICLE

Journal on Artificial Intelligence, Vol.1, No.1, pp. 29-36, 2019, DOI:10.32604/jai.2019.05939
Abstract In recent years, with the prosperity of world trade, the water transport industry has developed rapidly, the number of ships has surged, and ship safety accidents in busy waters and complex waterways have become more frequent. Predicting the movement of the ship and analyzing the trajectory of the ship are of great significance for improving the safety level of the ship. Aiming at the multi-dimensional characteristics of ship navigation behavior and the accuracy and real-time requirements of ship traffic service system for ship trajectory prediction, a ship navigation trajectory prediction method combining ship automatic identification system information and Back Propagation… More >

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10

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ARTICLE

Journal on Artificial Intelligence, Vol.1, No.2, pp. 89-99, 2019, DOI:10.32604/jai.2019.07885
Abstract Materials selection is a multiple attribute decision making (MADM) problem. A lot of MADM methods are applicable to materials selection, and it may produce considerable differences between the results of materials selection. But it is unknown which MADM method is better. So it is desirable to decide reasonable final result of materials selection in consideration of the individual results from different MADM methods. In this paper, materials selection method combined with different MADM methods is proposed. The method is based on final ranks of alternative materials, where the final ranks are determined from the ranks of the alternative materials using… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.1, No.1, pp. 1-8, 2019, DOI:10.32604/jai.2019.06064
Abstract Drone also known as unmanned aerial vehicle (UAV) has drawn lots of attention in recent years. Quadcopter as one of the most popular drones has great potential in both industrial and academic fields. Quadcopter drones are capable of taking off vertically and flying towards any direction. Traditional researches of drones mainly focus on their mechanical structures and movement control. The aircraft movement is usually controlled by a remote controller manually or the trajectory is pre-programmed with specific algorithms. Consumer drones typically use mobile device together with remote controllers to realize flight control and video transmission. Implementing different functions on mobile… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.2, No.3, pp. 125-135, 2020, DOI:10.32604/jai.2020.010501
Abstract When we use traditional computer vision Inspection technology to locate the vehicles, we find that the results were unsatisfactory, because of the existence of diversified scenes and uncertainty. So, we present a new method based on improved SSD model. We adopt ResNet101 to enhance the feature extraction ability of algorithm model instead of the VGG16 used by the classic model. Meanwhile, the new method optimizes the loss function, such as the loss function of predicted offset, and makes the loss function drop more smoothly near zero points. In addition, the new method improves cross entropy loss function of category prediction,… More >

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Open Access

ARTICLE

Journal on Artificial Intelligence, Vol.1, No.2, pp. 59-68, 2019, DOI:10.32604/jai.2019.06346
Abstract In order to solve the problem that real-time face recognition is susceptible to illumination changes, this paper proposes a face recognition method that combines Local Binary Patterns (LBP) and Embedded Hidden Markov Model (EHMM). Face recognition method. The method firstly performs LBP preprocessing on the input face image, then extracts the feature vector, and finally sends the extracted feature observation vector to the EHMM for training or recognition. Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate. More >

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ARTICLE

Journal on Artificial Intelligence, Vol.1, No.2, pp. 69-88, 2019, DOI:10.32604/jai.2019.06535
Abstract This paper develops a joint model utilizing the principal component analysis (PCA) and the back propagation (BP) neural network model optimized by the Levenberg Marquardt (LM) algorithm, and as an application of the joint model to investigate the damages caused by typhoons for a coastal province, Fujian Province, China in 2005-2015 (latest). First, the PCA is applied to analyze comprehensively the relationship between hazard factors, hazard bearing factors and disaster factors. Then five integrated indices, overall disaster level, typhoon intensity, damaged condition of houses, medical rescue and self-rescue capability, are extracted through the PCA; Finally, the BP neural network model,… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.2, No.1, pp. 17-27, 2020, DOI:10.32604/jai.2020.010132
Abstract Deep learning has made a great breakthrough in the field of speech and image recognition. Mature deep learning neural network has completely changed the field of nat ural language processing (NLP). Due to the enormous amount of data and opinions being produced, shared and transferred everyday across the Internet and other media, sentiment analysis has become one of the most active research fields in natural language processing. This paper introduces three deep learning networks applied in IMDB movie reviews sent iment analysis. Dataset was divided to 50% positive reviews and 50% negative reviews. Recurrent Neural Network (RNN) and Long Short-Term… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.2, No.3, pp. 113-124, 2020, DOI:10.32604/jai.2020.010137
Abstract In recent years, the problem of “Impolite Pedestrian” in front of the zebra crossing has aroused widespread concern from all walks of life. The traffic sector’s governance measures have become more serious. The traditional way of governance is onsite law enforcement, which requires a lot of manpower and material resources and is low efficiency. An enhanced YOLOv3-tiny model is proposed for pedestrians and vehicle detection in traffic monitoring. By modifying the backbone network structure of YOLOv3- tiny model, introducing deep detachable convolution operation, and designing the basic residual block unit of the network, the feature extraction ability of the backbone… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.3, No.1, pp. 1-8, 2021, DOI:10.32604/jai.2021.014175
Abstract Deep neural networks (DNNs) are widely adopted in daily life and the security problems of DNNs have drawn attention from both scientific researchers and industrial engineers. Many related works show that DNNs are vulnerable to adversarial examples that are generated with subtle perturbation to original images in both digital domain and physical domain. As a most common application of DNNs, face recognition systems are likely to cause serious consequences if they are attacked by the adversarial examples. In this paper, we implement an adversarial attack system for face recognition in both digital domain that generates adversarial face images to fool… More >

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ARTICLE

Journal on Artificial Intelligence, Vol.1, No.1, pp. 19-27, 2019, DOI:10.32604/jai.2019.05817
Abstract In order to acquire the degradation state of rolling bearings and achieve predictive maintenance, this paper proposed a novel Remaining Useful Life (RUL) prediction of rolling bearings based on Long Short Term Memory (LSTM) neural net-work. The method is divided into two parts: feature extraction and RUL prediction. Firstly, a large number of features are extracted from the original vibration signal. After correlation analysis, the features that can better reflect the degradation trend of rolling bearings are selected as input of prediction model. In the part of RUL prediction, LSTM that making full use of the network’s memory in time… More >

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