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Systems For Identifying And Segmenting Facial Labels 3

Systems For Identifying And Segmenting Facial Labels

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3rd international conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2023

作者： Kumar, Pavan Sobti, Rajeev Tyagi, Swati Singh, Rajesh Swathi, Bajila Tiwari, Mohit Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Department of Information Technology Hyderabad India Lovely Professional University Phagwara India University of Delaware NewarkDE United States Uttaranchal University Uttaranchal Institute of Technology India Sr University School of Computer Science and Artificial Intelligence Telangana Warangal India Bharati Vidyapeeth's College of Engineering Department of Computer Science and Engineering Delhi India

ISBN: (纸本)9798350399264

To perform precise facial labelling, we suggest an edge-to-edge identification method in this study. According to their cutting-edge efficiency, fully convolutional networks have replaced other common algorithms in the domain of semantic categorization. Nevertheless, a broad FCN typically yields uniform and slick outcomes. Additionally, characteristics for some subcategories cannot be properly examined by FCN whenever the semantics categorization in collections, such as the face classification issue, is excessively imbalanced. To solve these issues, a pyramidal FCN initially encodes a face picture into multi-level characteristic mappings. Next, the characteristics of the various facial characteristics are retrieved independently using the enclosing box that a one-stage detecting head provides. The retrieved characteristics are processed by 3 category sub-networks to produce the appropriate segmentation accuracy. Direct decoding of the layer of skin is possible first from pyramidal FCN's rear end. The total segmented output is then produced by integrating the several sections. Furthermore, the suggested approach, which was tested on a database with only one face labelled row, may be utilized immediately to carry out complex multi-facial classification tasks without requiring any networking modifications or extra modules or data. With a modest size of the networking, the entire system can be taught from beginning to finish (12 MB). Studies demonstrate that the suggested strategy can produce more precise (one or multiple) facial labelling outcomes in comparison to earlier efforts and achieves cutting-edge outcomes inside the HELEN facial database.. © 2023 IEEE.

关键词： Face recognition

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Proceedings of the 2022 3rd international conference on Intelligent Computing, Instrumentation and Control Technologies: Computational intelligence for Smart Systems, ICICICT 2022

Proceedings of the 2022 3rd International Conference on Inte...

引用

3rd international conference on Intelligent Computing, Instrumentation and Control Technologies, ICICICT 2022

ISBN: (纸本)9781665410052

The proceedings contain 311 papers. The topics discussed include: exploration of performance of dynamic branch predictors used in mitigating cost of branching;a comparative study of ant colony optimization and genetic algorithm for path planning of aerial food delivery system;energy management, design constraints and solution for data dissemination in wireless sensor networks;a case study of BIM based approach for electrical installation detail drafting;design of self-tuning fuzzy Pi controller for MIMO process using an analytical approach for selecting the scaling factors;blood donor management system - an android based model and implementation;hybrid network security model for small and mid-sized enterprises;an approach for p2p based botnet detection using machine learning;a pilot investigation on the performance of auditory stimuli based on EEG signals classification for BCI applications;disease classification techniques – a survey;a reliable control system for unmanned aircraft using fault-tolerant control;a review on thermal infrared semantic distribution for nightfall drive;deep convolution neural network in classification of liver tumor as benign or malignant from abdominal computed tomography;and waste management and wealth generation through waste elimination.

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Distinguishing Relational pattern Languages With a Small Number of Short Strings 33

Distinguishing Relational Pattern Languages With a Small Num...

引用

33rd international conference on Algorithmic Learning Theory (ALT)

作者： Holte, Robert C. Mousawi, S. Mahmoud Zilles, Sandra Univ Alberta Edmonton AB Canada Amii Edmonton AB Canada Univ Regina Regina SK Canada

This paper studies the equivalence problem for relational pattern languages, where a relation imposes dependencies between the two strings with which two variables in a pattern can be replaced simultaneously. Our focus is on the question whether the non-equivalence of two relational patterns is witnessed by short strings, namely those generated by replacing variables in the patterns by strings of length bounded by some (small) number z. After establishing a close connection between this problem and the study of the notions of teaching dimension and no-clash teaching dimension, we investigate specific classes of relational pattern languages. We show that the smallest number z that serves as a bound for testing equivalence is 2 when the relation between variable substitutions is that of equal string length, and the alphabet size it at least 3. This has interesting implications on the size and form of non-clashing teaching sets for the corresponding languages. By contrast, not even z = 3 is sufficient when the constraints require two substituted strings to be the reversal of one another, for alphabets of size 2. We conclude with a negative result on erasing pattern languages.

关键词： pattern languages equivalence problem teaching dimension

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Estimating Change Intensity and Duration in Human Activity recognition Using Martingales 7th

Estimating Change Intensity and Duration in Human Activity R...

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7th international conference on machine Learning, Optimization, and Data Science (LOD) / 1st Symposium on Artificial intelligence and Neuroscience (ACAIN)

作者： Etumusei, Jonathan Carracedo, Jorge Martinez McClean, Sally Ulster Univ Shore Rd Jordanstown BT37 0QB North Ireland

ISBN: (纸本)9783030954673;9783030954666

The subject of physical activity is becoming prominent in the healthcare system for the improvement and monitoring of movement disabilities. Existing algorithms are effective in detecting changes in data streams but most of these approaches are not focused on measuring the change intensity and duration. In this paper, we improve on the geometric moving average martingale method by optimising the parameters in the weighted average using a genetic algorithm. The proposed approach enables us to estimate the intensity and duration of transitions that happen in human activity recognition scenarios. Results show that the proposed method makes some improvement over previous martingale techniques.

关键词： Martingales Change detection Human activity recognition

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Flatter Minima of Loss Landscapes Correspond with Strong Corruption Robustness 27th

Flatter Minima of Loss Landscapes Correspond with Strong C...

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27th international conference on pattern recognition, ICPR 2024

作者： Zhong, Liqun Zhu, Kaijie Yang, Ge School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Science Beijing100190 China

ISBN: (纸本)9783031781063

To develop deep neural networks (DNNs) that maintain strong performance under different natural image corruptions such as noise and blur, namely with strong corruption robustness, is essential for real-world applications. Current methods to enhance corruption robustness focus primarily on data augmentation. But these methods are often empirically designed without a clear theoretical foundation. Here, we show that flatter minima of loss landscapes generally correspond with stronger corruption robustness. Based on this finding, we have developed a method named LASAM-DA that combines layer adaptive sharpness-aware minimization(LASAM) with data augmentation (DA) to boost corruption robustness. LASAM pushes DNNs towards flat minima of loss landscapes, while DA guides DNNs to memorize diverse data distributions. LASAM and DA reinforce each other without interference. Experiments on CIFRA-10-C, CIFAR-100-C and Tiny-ImageNet-C show that LASAM-DA outperforms competing methods and achieves state-of-the-art performance. LASAM-DA is versatile, not restricted to specific data types, network architectures or data augmentation methods. Code is openly accessible at https://***/cbmi-group/Flatter-Minima-Helps-for-Robustness. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep neural networks

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Research on Automatic Guided Vehicle Scheduling Strategies based on Artificial Intelligent 3

Research on Automatic Guided Vehicle Scheduling Strategies b...

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3rd international conference on Control and Intelligent Robotics, ICCIR 2023

作者： Wang, Chenke School of Intelligence science and technology University of Science and Technology Beijing China

ISBN: (纸本)9781510671867

Automatic guided vehicles have widely utilized in the transportation works and assist to move the objects into certain areas. Therefore, avoiding the conflict of these vehicles and determine the effective scheduling strategies are an essential component to improve the effectiveness and guarantee the safe of these vehicles. Existing scheduling strategies are concentrated to utilize the mathematical models or train a machine learning algorithm to dispose the scheduling for each vehicles. In this work, we utilize the artificial neural network to solve the scheduling issue and achieve the high effectiveness of moving vehicles. Initially, we order the vehicles with the principle of priority and get the minimum Euclid distance for these vehicles. Subsequently, an artificial neural network is trained to obtain the scheduling routes for each vehicles. From our extensive simulation results and comparison analysis, we can conclude our proposed model can effectively achieve the scheduling routes for each vehicles and avoid the conflict or congestion among guided vehicles with reasonable computation and response time. © 2023 SPIE.

关键词： Automatic guided vehicles

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GLSI Texture Descriptor Based on Complex Networks for Music Genre Classification

GLSI Texture Descriptor Based on Complex Networks for Music ...

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international Joint conference on Neural Networks (IJCNN)

作者： Coca Salazar, Andres Eduardo Fed Univ Technol Parana UTFPR TD Comp Engn Coordinat COENC Toledo PR Brazil

ISBN: (纸本)9781665488679

The texture classification of an image is related to an important musical attribute, the music genre. This relationship is depicted in the visual representation of the audio signal, called as spectrogram. In this paper, we propose a new Music Genre Classification (MGC) system that processes the spectrogram texture using the Gray Level and Structural Information (GLSI) descriptor, and represents the interconnection between the descriptor codes through complex networks. The GLSI descriptor is an improvement of the CLBP (Completed Local Binary pattern) descriptor, which quantifies the texture of an image with three codes: signal (CLBP-S), magnitude (CLBP-M), and central (CLBP-C). By transforming the CLBP-C code, GLSI adds macro-structural information. The network nodes represent the descriptor codes, and the respective edges, the relationship according to the horizontal and vertical consecutive condition. We defined two representations for the nodes: 1) individual code node, obtaining the G(s), G(m) and G(g) networks, and 2) triple code node, obtaining the G(smg) network. For the experimental stage, we used the GTZAN dataset, three types of spectrograms: conventional, mel-spectrogram and gammatonegram;and mining with network topological measures. For each type of spectrogram, we performed three experiments according to feature vector combinations, such as measures of: 1) G(s), G(m) and G(g), 2) G(smg), and 3) all networks. In the machine learning stage, we used the ensemble classifier Bagging with Random Forest, and 10fold cross-validation repeated 100 times. The experiment using all measures and all spectrograms revealed a satisfactory result, indicating that the MGC proposed is promising. We also propose a new equation to calculate the GLSI code, which proved to be much faster and with more intuitive encoding.

关键词： Digital image processing computer vision applications pattern recognition performance evaluation

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A Systematic Survey of Human Ear Biometrics recognition by using 2D images

A Systematic Survey of Human Ear Biometrics Recognition by u...

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Sciences and Techniques of Automatic Control and Computer Engineering MI-STA, IEEE international Maghreb Meeting of the conference on

作者： Howayda Abedallah Elmarzaki Bothaina F. Gargoum Amina A Abdo Department of Software Engineering University of Benghazi Benghazi Libya Department of Computer Science University of Benghazi Benghazi Libya Department of Artificial Intelligence Collage of Computer Technology Benghazi Libya

Nowadays, one of the most serious issues is secure verification, especially with the advent of artificial intelligence and machine learning and deep learning algorithms. As a result, the research field of recognizing human biometrics has grown significantly, and various types of algorithms have been proposed to help with security. From the available literature, we noticed that researchers were focusing on various systematic surveys for the recognition of human biometrics, including faces, eyes, finger prints, palms, and etc. Despite the popularity of machine and deep learning methods in the field of human hearing prediction, surveys of such methods are rare. In this work, we present an up-to-date survey of the ear recognition field by using 2D images and display the most relevant papers from the most popular databases by applying different techniques based on several criteria. This review presents an overview of the similarities and differences between different works and provides a statistical analysis view of common techniques commonly used in ear recognition literature. The results presented in this report provide insight on the patterns of this field's research.

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Design and Simulation of Intelligent Cross-border E-commerce Logistics System Based on Genetic Algorithm Technology of Artificial intelligence 3

Design and Simulation of Intelligent Cross-border E-commerce...

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3rd international conference on Electronics Technology and Artificial intelligence, ETAI 2024

作者： Chen, Xiaojuan Lei, Shixin Lei, Fei School of Management Guangdong University of Science & Technology Dongguan523083 China Management Consulting Division Dongguan Jiuxing Enterprise Management Consulting Co. Dongguan523000 China School of Finance and Economics Guangdong University of Science & Technology Dongguan523083 China

ISBN: (纸本)9781510683143

With the rapid development of cross-border e-commerce, the logistics system behind it faces various challenges such as complex routes, diverse transportation modes, and unpredictable customs clearance procedures. To address these challenges, this study proposes a design and simulation of an intelligent cross-border e-commerce logistics system based on genetic algorithm technology of artificial intelligence. The proposed system utilizes genetic algorithm techniques to optimize the logistics route planning, transportation mode selection, and customs clearance process. The genetic algorithm is employed to search for the optimal combination of routes, transportation modes, and customs procedures, considering various factors such as cost, time, and reliability. The system takes into account real-time data, including transportation costs, transit times, customs regulations, and historical shipment information, to make informed decisions and continuously improve the logistics efficiency. The simulation of the proposed system is conducted using historical cross-border e-commerce shipment data. The system is evaluated based on performance metrics such as transportation cost, delivery time, and customer satisfaction. The results demonstrate that the intelligent cross-border e-commerce logistics system based on genetic algorithm technology can effectively optimize the logistics process, reduce costs, and improve customer satisfaction. © 2024 SPIE.

关键词： Genetic algorithms Artificial intelligence Design intelligence systems Computer simulations Evolutionary algorithms Mathematical optimization Transportation Algorithm development Particle swarm optimization

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An Incentive-driven Edge intelligence Based on Stackelberg Game 3

An Incentive-driven Edge Intelligence Based on Stackelberg G...

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3rd international conference on Electronics and Communication;Network and Computer Technology (ECNCT)

作者： Hang, WangZhao Ming, XiaGe Jian, Chen Natl Univ Def Technol Coll Comp Sci & Technol Changsha Peoples R China

ISBN: (数字)9781510652118

ISBN: (纸本)9781510652118;9781510652101

Compared with cloud computing, edge computing shows real-time, security and other advantages when dealing with the explosive growth of the Internet of Things. In the process of data processing and mining data value, edge intelligence combines the advantages of edge computing and artificial intelligence to become a research hotspot. Federated learning is one of the most popular machine learning frameworks for edge intelligence. It provides stronger privacy protection for the client through the aggregation of the server-side client-side model. However, the latter often do not participate in the federal learning system due to resource constraints and economic considerations. Therefore, incentive mechanisms are necessary to attract higher quality clients. To this end, we use the Stackelberg game model to model the server and the client, and establish an incentive-driven federated learning algorithm FEDID. Finally, we verified the effectiveness of the incentive mechanism through experiments.

关键词： Incentive Mechanism Federated Learning Stackelberg Game Edge intelligence

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