the fusion of computer vision and natural language processing (NLP) has given rise to the interdisciplinary field of automatic image captioning, which aims to generate descriptive text for images without human interve...
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Nowadays, Artificial intelligence (AI) is emerged strongly. AI applications are the future of computing, with numerous services and solutions. Machine learning (ML) and deep learning (DL) are the most important compon...
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ISBN:
(纸本)9798350354140;9798350354133
Nowadays, Artificial intelligence (AI) is emerged strongly. AI applications are the future of computing, with numerous services and solutions. Machine learning (ML) and deep learning (DL) are the most important components of AIemerged tools. Natural language processing (NLP) is that field related to incorporating AI tools for improving machine recognition of human natural languages. Text mining and information retrieval applications have become important in frequent intelligent business services. Semantic text matching (STM) is an important application of NLP and text mining. It produces an understanding of two or more text segments in terms of similarity and distance evaluation. In this survey, AI-based STM approaches that are introduced in the literature are reviewed. We present the importance of the STM field using intelligent methods, in addition to explaining the main STMbased concepts. We discuss various categories of STM that appear in surveyed papers, they are the type of language, the deep learning utilized models, question-answering interesting studies, and other smart techniques that were implemented for STM. Finally, we summarize this review by introducing an explanation of some recent papers, in addition to illustrating a comparison between them. the utilized dataset, implemented model, and resulted accuracy were the main points of that comparison.
the intelligent inspection robot is capable of performing autonomous inspection tasks in complex environments. the robot's path planning is the key issue affecting its performance and efficiency. this paper studie...
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this study delves into the advancement of intelligent decision-making in robotics through the integration of deep learning technologies. With robotics becoming increasingly vital in industry, healthcare, and household...
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Recently, many new technologies are being used in the manufacturing industry. Quality control holds a significant position across all industries. Deep learning techniques aid manufacturers in evaluating product qualit...
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Recently, many new technologies are being used in the manufacturing industry. Quality control holds a significant position across all industries. Deep learning techniques aid manufacturers in evaluating product quality, thereby reducing the quantity of defective items that make their way into the market. the research mainly focused on detection of conditions of the bearing. the reliability and lifespan of rolling bearings are greatly influenced by wear, a significant tribological process. through field examination of bearing failures resulting from wear, possible causes are identified, leading to necessary measures for reducing or eliminating wear. the process comprises collection of the images of surface of the bearing that includes possible defects identification with literature survey. Preprocessing of the collected images of both good and defective bearings was completed, and an image processing algorithm was developed using deep learning. the system was designed to analyze microscopic images and determine whether a bearing is in good condition or defective. Experimental results indicated the training dataset, cross-validation accuracy 89.91% and 91.89%, respectively.
Self-play theory is an important branch of reinforcement learning. Different levels of complexity in scenarios are also necessary to make reinforcement learning more sophisticated. In this paper, a new reinforcement l...
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the proceedings contain 84 papers. the topics discussed include: YONA: an intelligence question-answering system based on artificial intelligence;a hybrid model based on GAT and TAGCN for node classification;SRGCN: so...
ISBN:
(纸本)9798350343113
the proceedings contain 84 papers. the topics discussed include: YONA: an intelligence question-answering system based on artificial intelligence;a hybrid model based on GAT and TAGCN for node classification;SRGCN: social relationship graph convolutional network-based social network user geolocation prediction;dense pedestrian detection method based on improved YOLOv5;opening the black box: interpretable machine learning reveals the relationship between lexical diversity and writing quality;porting and optimization of electric power consumers anomaly behavior monitoring on ARM platform;short text similarity detection based on graph attention networks and knowledge augmentation;MSFF-Net: a multi-scale feature fusion network for hippocampus segmentation;research on pathoptimization of automated warehouse based on genetic algorithm;and modeling operational profile for ai systems: a case study on UAV systems.
作者:
Qin, JieliXiamen Inst Technol
Higher Educ Key Lab Flexible Mfg Equipment Integr Xiamen 361021 Peoples R China Xiamen Inst Technol
Sch Mech Elect & Informat Engn Xiamen 361021 Fujian Peoples R China
Withthe rapid development of the semiconductor industry, the process technology has become more complex, and it is increasingly important to maximize the control of defects in production and improve wafer yield. Defe...
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ISBN:
(纸本)9798350375084;9798350375077
Withthe rapid development of the semiconductor industry, the process technology has become more complex, and it is increasingly important to maximize the control of defects in production and improve wafer yield. Defects shown in Wafer Bin Maps (WBMS) are often strongly correlated with local system failures in production. In view of this, this paper proposes the convolutional neural networks (CNNs) architecture based on machine learning, and realizes the classification of hybrid defects by designing a separate classification model of minimum defects and using the probability analysis of recognition results. the purpose is to classify and statistics the faults of the wafer diagram fault diagram, perform yield analysis and calculation, identify defect types according to the wafer (fault pattern recognition), and take corresponding decisions to adjust the process in view of the systematic fault chip. the effectiveness of the method is proved by experiments, and the identification accuracy of single defects is higher, and the detection performance of mixed defects is also improved, and the overall performance is better.
Cryptography technology is widely used in various fields to protect information security, and the security evaluation of cryptographic modules or chips themselves is also receiving increasing attention. Side-channel a...
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ISBN:
(纸本)9798331530372;9798331530365
Cryptography technology is widely used in various fields to protect information security, and the security evaluation of cryptographic modules or chips themselves is also receiving increasing attention. Side-channel analysis is a method to extract sensitive information, such as secret keys, by analyzing side-information leaked during the operation of encryption devices. It largely avoids the complexity of traditional cryptanalysis, and greatly improves the efficiency of analysis attacks. In recent years, researchers have applied deep learning to side-channel analysis attacks, greatly improving the performance of analysis attacks. However, most deep learning methods still suffer from fast overfitting, slow convergence, and shallow feature extraction, and are only effective for specific scenarios. We propose a novel method LCAF based on Long-short term Memory (LSTM), Convolutional neural network (CNN), and self-attention mechanism. Experimental results on four different datasets show that our method outperforms the existing techniques, and can successfully recover the key with only few traces.
Hijaiyah is in the Quran. learning Hijaiyah letters is difficult. this study can aid hijaiyah letter learning. this study improves hijaiyah handwriting prediction by modifying Deep learning architecture, particularly ...
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