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Network objects

Andrew Birrell, Greg Nelson, Susan Owicki, Edward Wobber
1993 Proceedings of the fourteenth ACM symposium on Operating systems principles - SOSP '93  
A network object is an object whose methods can be invoked over a network. This paper describes the design, implementation, and early experience with a network objects system for Modula-3.  ...  The paper includes a thorough description of realistic marshaling algorithms for network objects.  ...  type, provided by the network object runtime.  ... 
doi:10.1145/168619.168637 dblp:conf/sosp/BirrellNOW93 fatcat:vsivsrs2rbaknh6thq4bmnmbdm

Object-Oriented Networking [article]

Panos Georgatsos, Paris Flegkas, Vasilis Sourlas, Leandros Tassiulas
2015 arXiv   pre-print
We propose the object-oriented networking (OON) framework, for meeting the generalized interconnection, mobility and technology integration requirements underlining the Internet.  ...  In OON, the various objects that need to be accessed through the Internet (content, smart things, services, people, etc.) are viewed as network layer resources, rather than as application layer resources  ...  Objects are identified by their i-name in the information networking layer. Physical-form names identify objects from a data networking perspective.  ... 
arXiv:1502.07495v1 fatcat:5esusegribantew5xnxulq3yaa

The neural network objects

Marcel Kunze, Johannes Steffens
1997 Nuclear Instruments and Methods in Physics Research Section A : Accelerators, Spectrometers, Detectors and Associated Equipment  
Neural Network Objects (NNO) is a C++ class library that implements the most popular conventional neural networks together with novel incremental models that have been invented at Bochum University.  ...  TrainEpoch and TestEpoch are functions to train and test networks with a complete set of vectors out of a TDataServe object.  ...  AllocNet acquires resources and is executed during network construction. InitNet sets up the network weight matrix.  ... 
doi:10.1016/s0168-9002(97)00031-4 fatcat:hatrv3q4ozhmhh4qdwrx75km4y

Object-Oriented Bayesian Networks [article]

Daphne Koller, Avi Pfeffer
2013 arXiv   pre-print
In this paper, we describe an object-oriented Bayesian network (OOBN) language, which allows complex domains to be described in terms of inter-related objects.  ...  We use a Bayesian network fragment to describe the probabilistic relations between the attributes of an object.  ...  Object-Oriented Bayesian Networks  ... 
arXiv:1302.1554v1 fatcat:wr7l4floa5ewjl3wizaik4gomy

Objection-Based Causal Networks [article]

Adnan Darwiche
2013 arXiv   pre-print
This paper introduces the notion of objection-based causal networks which resemble probabilistic causal networks except that they are quantified using objections.  ...  Objection-based causal networks enjoy almost all the properties that make probabilistic causal networks popular, with the added advantage that objections are, arguably more intuitive than probabilities  ...  DISCUSSION Objection-based causal networks resemble proba bilistic causal networks in their structure and be havior.  ... 
arXiv:1303.5400v1 fatcat:lv2buksccbfndd5kovlhortlkm

Stereo Object Matching Network [article]

Jaesung Choe, Kyungdon Joo, Francois Rameau, In So Kweon
2021 arXiv   pre-print
object-level information and achieve accurate depth performance near the object boundary regions.  ...  This paper presents a stereo object matching method that exploits both 2D contextual information from images as well as 3D object-level information.  ...  Illustration of stereo object matching network. Our network consists of three parts: (1) cost volume prediction, (2) 3D object detection, and (3) disparity regression.  ... 
arXiv:2103.12498v1 fatcat:4t75inxphzgv7flodtxagfkg3e

Object-Oriented Dynamic Networks [article]

Dmytro Terletskyi, Alexandr Provotar
2015 arXiv   pre-print
This paper contains description of such knowledge representation model as Object-Oriented Dynamic Network (OODN), which gives us an opportunity to represent knowledge, which can be modified in time, to  ...  build new relations between objects and classes of objects and to represent results of their modifications.  ...  dynamic network for these objects and classes of objects.  ... 
arXiv:1510.04194v1 fatcat:57qasobnrff5lcaa5g4wd4pew4

Multi-objective cooperative coevolution of artificial neural networks (multi-objective cooperative networks)

N Garcı́a-Pedrajas, C Hervás-Martı́nez, J Muñoz-Pérez
2002 Neural Networks  
MOBNET evolves subcomponents that must be combined in order to form a network, instead of whole networks.  ...  In this work we show how using several objectives for every subcomponent and evaluating its fitness as a multi-objective optimization problem, the performance of the model is highly competitive.  ...  Complexity (three objectives ). Three objectives play the role of a regularization term. These objectives penalize big networks with respect to smaller ones.  ... 
doi:10.1016/s0893-6080(02)00095-3 pmid:12425442 fatcat:z2pzopequvee7jcndu4eltfyv4

Object Guided External Memory Network for Video Object Detection

Hanming Deng, Yang Hua, Tao Song, Zongpu Zhang, Zhengui Xue, Ruhui Ma, Neil Robertson, Haibing Guan
2019 2019 IEEE/CVF International Conference on Computer Vision (ICCV)  
In this work, we propose the first object guided external memory network for online video object detection.  ...  Video object detection is more challenging than image object detection because of the deteriorated frame quality.  ...  Object Guided External Memory Network The proposed object guided external memory network N mem contains two external memory matrices M pix and M inst , and novel read, write operations, which are de-scribed  ... 
doi:10.1109/iccv.2019.00678 dblp:conf/iccv/DengHSZXMRG19 fatcat:64g5gnwxgjbpbbamdkdqdg5dmy

Relation Networks for Object Detection [article]

Han Hu, Jiayuan Gu, Zheng Zhang, Jifeng Dai, Yichen Wei
2018 arXiv   pre-print
It does not require additional supervision and is easy to embed in existing networks.  ...  This work proposes an object relation module.  ...  Relation Networks For Object Detection Review of Object Detection Pipeline This work conforms to the region based object detection paradigm.  ... 
arXiv:1711.11575v2 fatcat:hzqhbn5vbrhcpm4bts24e6lmky

Temporal and Object Quantification Networks [article]

Jiayuan Mao, Zhezheng Luo, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu, Leslie Pack Kaelbling, Tomer D. Ullman
2021 arXiv   pre-print
We present Temporal and Object Quantification Networks (TOQ-Nets), a new class of neuro-symbolic networks with a structural bias that enables them to learn to recognize complex relational-temporal events  ...  This is done by including reasoning layers that implement finite-domain quantification over objects and time.  ...  People have also used structural representations to model object-centric temporal concepts with graph neural networks [GNNs; , recurrent neural networks [RNNs; Ibrahim et al. 2016] , and integrated GNN-RNN  ... 
arXiv:2106.05891v1 fatcat:dp3l4srqbvbsxhx2lp476prxde

Distributed object technology for networking

J.-P. Redlich, M. Suzuki, S. Weinstein
1998 IEEE Communications Magazine  
objectives that network designers have to meet.  ...  The network applications shown in Fig. 1 are distributed objects interacting through platforms such as the Common Object Request Broker Architecture (CORBA) [l] and the Distributed Component Object Model  ...  Raychaudhuri for encouragement of our work on network software architecture.  ... 
doi:10.1109/35.722144 fatcat:dkp4k6j5i5ghpbion5fpexlsg4

Object location in realistic networks

Kirsten Hildrum, Robert Krauthgamer, John Kubiatowicz
2004 Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures - SPAA '04  
We devise an object location scheme that achieves a guaranteed low stretch in a wider and more realistic class of networks than previous schemes.  ...  As a byproduct, our scheme has several advantages over existing ones, such as robustness to errors in network measurements, and simpler design choices of system builders, which may lead to improved and  ...  Objects are placed in the network by their publisher node.  ... 
doi:10.1145/1007912.1007918 dblp:conf/spaa/HildrumKK04 fatcat:tltwwvjv7rbz5pe4ef72znm3ry

Managed Ecosystems of Networked Objects

Jeroen Hoebeke, Eli De Poorter, Stefan Bouckaert, Ingrid Moerman, Piet Demeester
2011 Wireless personal communications  
As a solution, we propose the concept of Managed Ecosystem of Networked Objects, which aims to create a smart network architecture for groups of Internet-connected objects by combining network virtualization  ...  In this paper, we evaluate the current efforts to integrate sensors and actuators into the Internet and identify the limitations at the level of cooperation of these Internet-connected objects and the  ...  This allows interaction between all sensors and other networked objects that need to cooperate.  ... 
doi:10.1007/s11277-011-0292-9 fatcat:3nnjqa6ntrdi3c4lkbohip574q

Moving Objects in Networks Databases [chapter]

Victor Teixeira de Almeida
2006 Lecture Notes in Computer Science  
Uncertain Moving Objects in Networks The most important type of moving object is the moving point object.  ...  These are the so called network constrained moving objects.  ...  Appendix A Nearest Neighbors in Spatial Network Databases One of the most important kinds of queries in Spatial Network Databases (SNDB) to support Location-Based Services (LBS) is the k-Nearest Neighbors  ... 
doi:10.1007/11896548_8 fatcat:iim3mtyzpveynh4rnpgub2g57u
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