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检索条件"任意字段=3rd International Conference on Object-Oriented Databases"

共 1176 条记录，以下是1-10 订阅

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3rd international conference on Deductive and object-oriented databases, DOOD 1993

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3rd international conference on Deductive and object-oriented databases, DOOD 1993

ISBN: (纸本)9783540575306

The proceedings contain 31 papers. The special focus in this conference is on Deductive and object-oriented databases. The topics include: Treating programs as objects: the computational proxy experience;foundations of aggregation in deductive databases;the differential fixpoint operator with subsumption;datalog with non-deterministic choice computes NDB-PTIME;a deductive and object-oriented approach to a complex scheduling problem;on the logical foundations of schema integration and evolution in heterogeneous database systems;explaining program execution in deductive systems;a logic for rule-based query optimization in graph-based data models;specifying rule-based query optimizers in a reflective framework;semantic query optimization in deductive object-oriented databases;research in deductive and object-oriented databases;an implementation overview of the aditi deductive database system;negation and aggregates in recursive rules: the LDL++ approach;a deductive language with negation for complex-object databases with hierarchies;on efficient reasoning with implication constraints;bottom-up query evaluation with partially ordered defaults;an extension of path expressions to simplify navigation in object-oriented queries;query classes;database updating revisited;applications of deductive and object-oriented databases;towards a reflective architecture of intelligent database systems;a deductive and typed object-oriented language;a language for declarative querying in an object-oriented database;tracking causal dependencies in an active object-oriented database;automatic class and method generation for object-oriented databases;modeling multilevel entities using single level objects;a model using classes as a basic organization tool;knowledge base revision using circumscription and versioning of objects in deductive databases.

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Lidar-Based Car Detection and Position Estimation Using Convolutional Neural Networks for Autonomous Driving

Lidar-Based Car Detection and Position Estimation Using Conv...

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Advancement in Computation & Computer Technologies (InCACCT), international conference on

作者： Jyothi Swaroop Arlagadda N Rambabu Penugonda Rohith Goura Independent Researcher Santa Clara USA Independent Researcher San Jose CA

ISBN: (数字)9798331543891

ISBN: (纸本)9798331543907

Despite the many applications of computer vision in robotics, automation, and self-driving cars, object detection remains a significant difficulty. Recent developments in object recognition and image classification, in particular convolutional neural networks (CNNs), have significantly aided in the development of neural networks that enable practical applications in autonomous driving. This study uses a modified CNN architecture designed for accurate 3-D item identification to examine vehicle recognition and spatial analysis utilizing LiDAR data. The network offers robust localization even in difficult environments with occlusions using point-based bounding box predictions. Using a RANSAC-based refinement technique, the suggested system achieved a classification accuracy of 96.71% with bounding box precision significantly enhanced after 246 epochs of extensive evaluation on the KITTI dataset. These results validate the model's strong generalization ability in real-world scenarios with mirrored, noisy, and variable-oriented data. The findings validate the growing significance of CNNs in addressing autonomous navigation challenges. By contributing to the development of safer and more reliable transportation networks, our work ultimately moves the road toward completely autonomous vehicles.

关键词： Accuracy Three-dimensional displays Roads Neural networks Transportation object detection Convolutional neural networks Reliability object recognition Noise measurement

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Proceedings of the 3rd international Workshop on Context-oriented Programming, COP'11 - Co-located with the 25th European conference on object-oriented Programming, ECOOP 2011

Proceedings of the 3rd International Workshop on Context-Ori...

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3rd international Workshop on Context-oriented Programming, COP'11 - Co-located with the 25th European conference on object-oriented Programming, ECOOP 2011

ISBN: (纸本)9781450308915

The proceedings contain 7 papers. The topics discussed include: featherweight EventCJ: a core calculus for a context-oriented language with event-based per-instance layer transition;safer context (de)activation - through the prompt-loyal strategy;a context management infrastructure with language integration support;JavaCtx: seamless toolchain integration for context-oriented programming;context-oriented programming for mobile devices: JCop on Android;implementing scoped method tracing with ContextJS;and CJAdviser: SMT-based debugging support for ContextJ*.

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Deep Learning based HOG ResNet Model for Group Attendance System in Educational Institutions

Deep Learning based HOG ResNet Model for Group Attendance Sy...

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Disruptive Technologies (ICDT), international conference on

作者： P Ravi Kiran Varma A Venkata Sriram CH Bharath B Sai Reddy Department of IT Sagi Rama Krishnam Raju Engineering College Bhimavaram India Department of IT (AI & DS) Sagi Rama Krishnam Raju Engineering College Bhimavaram India

ISBN: (数字)9798331519582

ISBN: (纸本)9798331519599

Traditional attendance management systems in educational institutions use manual methods that are time-consuming and prone to errors. This work proposes an automated attendance taking system implemented through group pictures using face recognition making the process much easier in classroom environments. For detection of faces from group photographs, the system employs Histogram of oriented Gradients (HOG) available in the dlib library. For face recognition, Deep learning architecture known as ResNet is used to identify the students under different poses and lighting conditions. A real-time dataset was created using various photographs of the students from different angles with the most common scenarios that are likely to happen in the real classroom situation. The facial recognition model was trained on this custom real-time dataset thus addressing the challenge of photography in the classroom conditions. Using group images, the system recognizes students present classes, marks the attendance and registers them in the attendance database in real time. A user-friendly interface was developed for efficient management of attendance records. Developed Group picture attendance system demonstrates high accuracy in attendance management in various conditions, featuring seamless database integration and a user-friendly front-end interface for data retrieval.

关键词： Deep learning Accuracy databases Face recognition Computational modeling Scalability Transformers Real-time systems Face detection Reliability

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Performance Enhancement of DBSCAN Density-Based Clustering Algorithm in Data Mining

Performance Enhancement of DBSCAN Density-Based Clustering A...

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international Symposium on Advanced Computing and Communication (ISACC)

作者： Neha Tyagi Rashmi Mishra Sitanshu Kumar Patel Somraj Karki Department of Computer Science and Engineering Amity University Noida India

ISBN: (数字)9798331523893

ISBN: (纸本)9798331523909

In order to facilitate better data analysis, clustering is a prominent data mining approach which separates data into separate categories based on their similarities and distinctions. It’s a method of unsupervised learning which may generate a model with a training dataset. Throughout this study, the Euclidian distance and EPS (Epsilon) value has been determined using the DBSCAN technique based on the similarities as well as disparity for the input data. Moreover, Euclidian distance is dynamically determined using the back propagation method; a simulation study is carried out that demonstrates both speed and precision improvements. DBSCAN, or spatial clustering based on density of application with noise, is a common clustering technique for geographic datasets that can locate clusters of any shape and automatically detect noise points. To deal with the problem, an improved DBSCAN technique based on the selection of features (FS-DBSCAN) has been suggested. However, the algorithm proved unstable while handling huge dimensional data. Many simulation via real-world datasets testify the algorithm’s efficiency. Comparison of the proposed algorithm to the DBSCAN algorithm demonstrates its benefits. Structures within the collections may be identified by dividing of collections of products into classes and clusters, with a focus on increasing the resemblances of objects within each cluster and lowering the similarities of things belonging to different clusters.

关键词： Backpropagation Training Machine learning algorithms Shape Noise Clustering algorithms Spatial databases Data mining object recognition Unsupervised learning

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Exploratory Data Analysis of Geolocation Data using Machine Learning

Exploratory Data Analysis of Geolocation Data using Machine ...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), international conference on

作者： A. Vinora S. Afrin Lavina Roshni Manoj A. Alagu Gomathi Department of Information Technology Velammal College of Engineering and Technology Madurai Tamilnadu

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Geographical location is the process of identifying an object or person's location with the help of technology. It uses various methods, such as GPS (Uses satellite signals to pinpoint a device's location globally, with an accuracy of 5–10 meters outdoors) Wi-Fi location (Relies on nearby Wi-Fi signals to estimate location, achieving 5–30 meters' accuracy, especially in urban and indoor settings) and IP positioning, to determine the latitude and length of a device or individual. Common uses of geolocation include navigation and location services, social media, electronic commerce, fleet management, and emergency services. The exploration analysis of geolocation data is an important aspect of gaining insights into the patterns and trends within the data. The problem arises when people move from one place to another and need to find the right place. The existing system includes hostels and apartments for rent, and it has purchased and sold options. It also does not recommend restaurants, gyms, etc. based on users' preferences. Previous research lacks the accuracy of the real recommendations. An algorithm called K- means clustering is used to classify certain data elements with certain properties. However, it has a drawback when the radii of two circular groups with the same average center diverge. Another is Hierarchical clustering. Actually, it is a very useful technique in exploratory analysis of geolocation data, since it discovers hierarchical relationships and structures within the spatial data set. The technique designs a hierarchy of clusters from bottom- up, which is known as agglomerative, or top-down, that is known as divisive. Agglomerative clustering is more commonly used.

关键词： Meters Accuracy Data analysis Systematics Navigation Social networking (online) Geology Urban planning Spatial databases Wireless fidelity

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Towards an inductive design of distributed object oriented databases 3

Towards an inductive design of distributed object oriented d...

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3rd IFCIS international conference on Cooperative Information Systems

作者： Baiao, F Mattoso, M Zaverucha, G Univ Fed Rio de Janeiro Dept Comp Sci COPPE BR-21941 Rio De Janeiro Brazil

ISBN: (纸本)0818683805

Cooperative Information Systems (CIS) often consist of applications that access shared resources such as databases. Since centralized systems may have a great impact on the system performance, parallel and distribution techniques are needed for attaining scalability. Distributed databases are, then, crucial for the development of cooperative applications. However, in order to improve performance, it is very important to design information distribution properly, which is the goal of Distribution Design. Considering the various difficulties embedded in the Design of Distributed object oriented databases, this work presents an algorithm to assist distribution designers in their task. The analysis algorithm indicates the most adequate fragmentation technique (vertical, horizontal or mixed) for each class in the database schema, and we propose the use of a machine learning method - inductive Logic Programming - to uncover some implicit issues to be considered in the distribution design, thus revising the proposed analysis algorithm.

关键词： design of distributed object oriented databases mired fragmentation inductive logic programming

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Intelligent hypermedia database

Intelligent hypermedia database

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3rd international conference on Signal Processing (ICSP 96)

作者： Wu, XY Qi, FH Institute of Optical Fiber Shanghai JiaoTong University China

ISBN: (纸本)7505338900

With the fast development of multimedia technology, efficient management of multimedia data has become more and more important. In this paper, a multimedia database is established. It has used hypermedia and object-oriented technology. Besides that, to realize intelligent retrieval such as semantic retrieval, I add a simple expert system into it. It can manage multimedia information such as sounds, images, texts and videos efficiently.

关键词： hypermedia multimedia computing deductive databases object-oriented databases information retrieval expert systems intelligent hypermedia database multimedia technolog efficient management multimedia data multimedia database object-oriented technology intelligent retrieval semantic retrieval expert system images text videos sounds

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An environment for teaching object-oriented programming: objectKarel

An environment for teaching object-oriented programming: Obj...

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3rd IEEE international conference on Advanced Learning Technologies

作者： Satratzemi, M Xinogalos, S Dagdilelis, V Univ Macedonia Dept Appl Informat Thessaloniki Greece

ISBN: (纸本)0769519679

In this paper we propose a new integrated programming environment, objectKarel, for teaching the object-oriented programming paradigm. Its main features are: a series of e-lessons, a special kind of structure editor, run-time error detection, program animation and recordability of students' actions. Finally, we describe the results of a pilot use of objectKarel to teach object-oriented programming to undergraduate students.

关键词： object oriented programming

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XML interface for object oriented databases 3

XML interface for object oriented databases

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3rd international conference on Enterprise Information Systems, ICEIS 2001

作者： VanLingen, Frank European Organization for Nuclear Research Geneva 23CH-1211 Switzerland

ISBN: (纸本)9729805024

Within CERN (European Organization for Nuclear Research) there are numerous heterogenous data sources (different in format, type and structure). Several of these sources will be flat files or data sources other than databases. To create a common interface to these sources, we decided to use XML (eXtended Markup Language) since XML is becoming the de facto standard for data exchange/integration. A significant part of CERN data is stored within object oriented databases. This document describes a mechanism to access object-oriented databases as an XML document by using serialization on demand and rewriting XML queries to OQL queries. To accomplish this the Xpath specification is extended and mapped on the object oriented paradigm.

关键词： XML

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