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1. |
Record Nr. |
UNINA9910983043103321 |
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Autore |
Lin Zhouchen |
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Titolo |
Pattern Recognition and Computer Vision : 7th Chinese Conference, PRCV 2024, Urumqi, China, October 18–20, 2024, Proceedings, Part V / / edited by Zhouchen Lin, Ming-Ming Cheng, Ran He, Kurban Ubul, Wushouer Silamu, Hongbin Zha, Jie Zhou, Cheng-Lin Liu |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2025 |
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ISBN |
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Edizione |
[1st ed. 2025.] |
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Descrizione fisica |
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1 online resource (641 pages) |
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Collana |
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Lecture Notes in Computer Science, , 1611-3349 ; ; 15035 |
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Altri autori (Persone) |
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ChengMing-Ming |
HeRan |
UbulKurban |
SilamuWushouer |
ZhaHongbin |
ZhouJie |
LiuCheng-Lin |
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Disciplina |
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Soggetti |
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Image processing - Digital techniques |
Computer vision |
Artificial intelligence |
Application software |
Computer networks |
Computer systems |
Machine learning |
Computer Imaging, Vision, Pattern Recognition and Graphics |
Artificial Intelligence |
Computer and Information Systems Applications |
Computer Communication Networks |
Computer System Implementation |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This 15-volume set LNCS 15031-15045 constitutes the refereed proceedings of the 7th Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2024, held in Urumqi, China, during October 18–20, 2024. The 579 full papers presented were carefully reviewed and selected from 1526 submissions. The papers cover various topics in the broad areas of pattern recognition and computer vision, including machine learning, pattern classification and cluster analysis, neural network and deep learning, low-level vision and image processing, object detection and recognition, 3D vision and reconstruction, action recognition, video analysis and understanding, document analysis and recognition, biometrics, medical image analysis, and various applications. |
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2. |
Record Nr. |
UNINA9910878059903321 |
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Autore |
Dehuri Satchidananda |
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Titolo |
Machine Intelligence, Tools, and Applications : Proceedings of the International Conference on Machine Intelligence, Tools, and Applications—ICMITA 2024 / / edited by Satchidananda Dehuri, Sung-Bae Cho, Venkat Prasad Padhy, Poonkuntrun Shanmugam, Ashish Ghosh |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (435 pages) |
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Collana |
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Learning and Analytics in Intelligent Systems, , 2662-3455 ; ; 40 |
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Altri autori (Persone) |
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ChoSung-Bae |
PadhyVenkat Prasad |
ShanmugamPoonkuntrun |
GhoshAshish |
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Disciplina |
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Soggetti |
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Computational intelligence |
Artificial intelligence |
Machine learning |
Computational Intelligence |
Artificial Intelligence |
Machine Learning |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Fuzzy Guided Genetic Algorithm Routing for Energy Conservation in Wireless Sensor Networks -- Comparative Analysis of Prediction Models for Software Bug Prediction -- Mandelbug Classification Engine Transfer Learning and NLP Approach -- Software Maintenance Prediction Using Regression Models -- Rough Set ELM Classifier and Deep Architecture for Remote Sensing Images -- Design of an Efficient Model for Satellite Image Classification Using Graph Neural Networks and Elephant Herding Optimization -- Multifaceted Analysis of Climate Trends and Air Quality in Indian Metropolises A Machine Learning and Time Series Forecasting Approach -- Machine Learning based Analysis and Forecasting of Electricity Demand in Misamis Occidental Philippines -- Implementation and Optimization of Swarm based System for Multi Agent Coordination and Task Execution in Marine Environment -- Implementing Deep NN for Plant Disease Detection and Diagnosis -- A PSO approach for two warehouse inventory problem with imperfect quality and variable discount -- Design of Intraday Stock Price Prediction Model using Machine Learning via Technical Indicators. |
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Sommario/riassunto |
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This book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML). This would enable the readers with a strong understanding of critical issues in ML by providing both broad and detailed perspectives on cutting-edge theories, algorithms, and tools. This will become a single source of reference on conceptual, methodological, technical, and managerial issues, as well as provide insight into emerging trends and future opportunities in the discipline of ML. This book contains altogether 36 chapters in the area of ML and its applications. |
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