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检索条件"主题词=Software algorithms"

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Continuous learning with random memory for object detection in robotic applications

Continuous learning with random memory for object detection ...

引用

Nonlinearity, Information and Robotics, (NIR) International Conference

作者： Ivan Nenakhov Ruslan Mazhitov Kirill Artemov SeyedHassan Zabihifar Aleksandr Semochkin Sergey Kolyubin ITMO University St. Petersburg Russia PJSC Sberbank Moscow Russia Innopolis University Innopolis Russia

ISBN: (纸本)9781665424080

If the robot is to interact with environment designed for humans it has to be able to cope with new objects in it’s surrounding, and not only to classify but also effectively localize objects in its reach based on visual sensing. We cannot predict all objects the robot will face. So it needs to learn them while operating, without an external update of software. One of the promising approaches to handle this task is using detectors based on convolution neural networks (CNN) with continuous learning setup. However, there is a well-known problem of catastrophic forgetting (CF) that negatively affects accuracy of neural networks, the main algorithms in object recognition nowadays. Moreover, we need to reach a trade off between training time (because it is unacceptable if the robot trains for hours) and good acccuracy of detection. In this paper we review some of the latest approaches in the field and adapt one of SOtA methods in classification task to detection task. Particularly, we adapt YOLOv5 to work in scenario with continuous learning by adding random memory mechanism from [1] and applying layer freezing in order to increase training speed. We benchmark the proposed method using iCubWorld Transformations dataset and report results with significantly improved metrics and inference speed.

关键词： Training Visualization Neural networks software algorithms Object detection Robot sensing systems software

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Mining for Graph-Based Library Usage Patterns in COBOL Systems

Mining for Graph-Based Library Usage Patterns in COBOL Syste...

引用

IEEE International Conference on software Analysis, Evolution and Reengineering (SANER)

作者： Ruben Opdebeeck Johan Fabry Tim Molderez Jonas De Bleser Coen De Roover Vrije Universiteit Brussel Belgium Raincode Labs Belgium

When migrating legacy systems to more contemporary platforms, it is not always feasible to migrate their external library dependencies as well. A workaround can be to partially reimplement the library dependencies on the new platform, limiting oneself to the features that are used by the migrated system. For contemporary programming languages, several approaches to mining for library usage patterns have been proposed. For legacy programming languages, in contrast, such tools are lacking. This encumbers establishing what parts of a library need to be rewritten during a migration project, especially when considering large-scale *** this industry track paper, we present an approach to mining library usage patterns in COBOL code. We describe a library usage extractor for COBOL, which produces graphs that capture the control and data flow involved in library calls. The extractor supports legacy control flow features, such as GO TO. We use these graphs as input to two state-of-the-art frequent subgraph mining algorithms, and report on the scalability of their use for mining common library usage patterns in two industrial COBOL systems. The mined library usage patterns can help assess and subsequently steer the migration effort.

关键词： Industries Computer languages Limiting Scalability software algorithms Tools Feature extraction

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Pylot: A Modular Platform for Exploring Latency-Accuracy Tradeoffs in Autonomous Vehicles

Pylot: A Modular Platform for Exploring Latency-Accuracy Tra...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Ionel Gog Sukrit Kalra Peter Schafhalter Matthew A. Wright Joseph E. Gonzalez Ion Stoica UC Berkeley

We present Pylot, a platform for autonomous vehicle (AV) research and development, built with the goal to allow researchers to study the effects of the latency and accuracy of their models and algorithms on the end-to-end driving behavior of an AV. This is achieved through a modular structure enabled by our high-performance dataflow system that represents AV software pipeline components (object detectors, motion planners, etc.) as a dataflow graph of operators which communicate on data streams using timestamped messages. Pylot readily interfaces with popular AV simulators like CARLA, and is easily deployable to real-world vehicles with minimal code *** reduce the burden of developing an entire pipeline for evaluating a single component, Pylot provides several state-of-the-art reference implementations for the various components of an AV pipeline. Using these reference implementations, a Pylot-based AV pipeline is able to drive a real vehicle, and attains a high score on the CARLA Autonomous Driving Challenge. We also present several case studies enabled by Pylot, including evidence of a need for context-dependent components, and per-component time allocation. Pylot is open source, with the code available at https://***/erdos-project/pylot.

关键词： Codes Runtime Pipelines software algorithms Reinforcement learning Detectors Resource management

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Research on intelligent manufacturing equipment visual inspection control based on machine vision

Research on intelligent manufacturing equipment visual inspe...

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IEEE International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Chunyan Huo Tianshu Li Harbin Huade University Harbin Heilongjiang China

ISBN: (纸本)9781665428408

Enterprise mass production and zero waste control require on-line automatic detection in production and processing. Machine vision plays a key role in automatic detection. In recent years, with the development of economy and the progress of science and technology, the level of production and manufacturing technology has made remarkable achievements, and industrial robots are more and more widely used in the field of production and manufacturing. With the wide application of industrial robots, the technical level of industrial robots has also made significant progress. At present, industrial robots have higher functionality and stability, and industrial robots have also introduced visual monitoring technology, which makes the manufacturing field more intelligent. In order to meet the huge demand of the intelligent manufacturing equipment industry for machine vision technology, this paper combines the technical characteristics of equipment and special application environment to propose a general machine vision inspection and control technology system, which makes up for the current research deficiencies.

关键词： Manufacturing industries Visualization Service robots Machine vision software algorithms Production Manufacturing

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Development of Algorithm for Treatment of Extreme Outliers in Numerical Data, Conditional on Joint Distribution Relationship

Development of Algorithm for Treatment of Extreme Outliers i...

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International Scientific-Practical Conference Problems of Infocommunications Science and Technology

作者： Nikola Iliychev Iliev Marin Marinov Sergey Radukanov Raiffeisenbank Bulgaria Sofia Bulgaria D.A. Tsenov Academy of Economics Svishtov Bulgaria St. Cyril and St. Methodius University of Veliko Tarnovo Veliko Tarnovo Bulgaria

ISBN: (纸本)9781665406833

The paper describes the development of a model for treating extreme outliers in numerical data variables, using an alternative point of view - relationship conditional on data variables' joint distribution. The mentioned algorithm finds its roots in existing practices like Winsorization (or truncation) of extreme outliers independently for each variable. After establishing an overview of historical outlier treating, the authors turn their attention towards common erroneous assumptions, that, while often, being made, bring research analysis and conclusions towards big caveats. A common example is a joint distribution relationship shape's shift from that of a circular towards a rectangular shape, unexplainable or indefensible by statistics. Next the paper makes some propositions how to fix this prominent problem, by looking at existing joint distribution relationship's shape and how it could give insight on outlier treatment. Following that, the authors try to circumscribe a methodology for application of the proposed fix by going through the algorithm's mathematical specifics and assumptions. Lastly the paper studies the algorithm's application results, including possibilities for future studies, including interdisciplinary application within programing environment, for the possible purpose of creating an actual software solution.

关键词： Shape Statistical analysis software algorithms Data processing Data models software Mathematical models

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Mathetamical Model Using Denavit-Hartenberg Algorithm For Kinematic Control of 12DOF Zoomorphic Robot

Mathetamical Model Using Denavit-Hartenberg Algorithm For Ki...

引用

Machine Learning and Applied Network Technologies (ICMLANT), IEEE International Conference on

作者： Dennys Fernando Cantarero Urbina Alicia María Reyes Duke Universidad Tecnológica Centroamericana UNITEC Honduras

ISBN: (纸本)9781665449519

Walking zoomorphic robots have a great advantage compared to other types of mobile robots thanks to their structure and high adaptability in many areas, and it is thanks to this adaptability that it generates many possibilities of implementation but, due to their locomotion system they tend to be complex to develop since the use of various actuators for their movement and control is taken into account, so to solve these problems, the implementation of algorithms and mathematical models are used because that define the characteristics of the structure and of the various actions that must be taken into account to carry out a movement in a simplified and understandable way. The present research was carried out through the implementation of the spiral methodology for the development of a mathematical model that defines the kinematic control for this type of robot where, through both inverse and forward kinematic analysis, the position and orientation of the robot were described by applying the Denavit-Hartenberg algorithm, as well as the use of polynomial interpolators for the tracking of trajectories, which was verified by using Matlab and Robotics Toolbox software simulating movement that the robot will perform with the different extremities, determining said movement with the establishment of speeds and times in the joints.

关键词： Legged locomotion Analytical models Actuators Tracking software algorithms Kinematics Mathematical models

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Local filter-based sequential and distributed fusion state estimation for nonlinear multi-sensor systems with asynchronously correlated noises

Local filter-based sequential and distributed fusion state e...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Kun Yang Yao Zhang Yang Liu Jun–Tao Liu Kai Zhao Beijing Institute of Astronautical systems Engineering Northwestern Polytechnical University Beijing Institute of Astronautical systems Engineering

ISBN: (纸本)9781665478373

In this paper, sequential and distributed fusion state estimation algorithms based on local filter are proposed for nonlinear multi-sensor systems with asynchronously correlated noises. At first, in order to avoid the computational burden of measurement augmentation in centralized fusion filter, a sequential fusion filter is deduced by correcting measurement noises recursively. Subsequently, considering the problem that the parameters in covariance intersection (CI) fusion algorithm are difficult to estimate and the estimation accuracy of the sequential fast CI (SFCI) fusion algorithm is poor, a novel distributed fusion filter is proposed, where local filters are sent to the fusion center as the measurements and fusion predictor in the fusion center is sent to local filters by feedback. Then, to be suitable for practical applications, the numerical implementation based on third-degree spherical-radial rule is given. Finally, the superiority of the proposed algorithms is shown by using a nonlinear model.

关键词： software algorithms software quality Filtering algorithms Prediction algorithms Numerical models software reliability Noise measurement

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Description and Application of Network and Terminal Security Device Based on the Block Algorithm of Cryptographic Transformation of Information Using Random Keys

Description and Application of Network and Terminal Security...

引用

IEEE International Conference on Advanced Trends in Information Theory (ATIT)

作者： Ihor Pampukha Genadiy Zhyrov Volodymyr Druzhynin Ivan Chetverikov Serhey Lienkov Larysa Komarova Military Institute Taras Shevchenko National University of Kyiv Kyiv Ukraine Radiophysics Electronics and Computer Systems Taras Shevchenko National University of Kyiv Kyiv Ukraine National Aviation University Kyiv Ukraine National Academy of the Security Service of Ukraine Kyiv Ukraine

ISBN: (纸本)9781665406673

This article describes a device for protecting information that is transmitted over various telecommunications channels. The device protects networks and terminals uses a block algorithm for cryptographic transformation of information using random keys. Information protection device is designed for hardware, software or software-hardware implementation that meets the cryptographic requirements and by its characteristics provides the ability to protect confidential information in the network. The device also allows to protect user terminals from virus attacks in case of unauthorized access (hackers, viruses).The article also describes the possible areas of its practical application in different types of performance: telephony, data transmission over the Internet, identification systems, security systems, communication systems, protection of bank accounts and transactions, etc.

关键词： Computer viruses software algorithms Telephony software Internet Telecommunications software reliability

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Implementation of An Energy-Efficient Binary Square Rooter Using Reversible Logic By Applying The Non-Restoring Algorithm

Implementation of An Energy-Efficient Binary Square Rooter U...

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Communication, Computing and Industry 4.0 (C2I4), International Conference on

作者： S. Swathi S. Sushma V. Bindusree L Babitha Goud K. Sukesh S. China Venkateswarlu V. Vijay Rajeev Ratna Vallabhuni Institute of Aeronautical Engineering Dundigal Hyderabad India Bayview Asset Management LLC Florida USA

ISBN: (纸本)9781665420143

Calculation of square root will be an essential mathematical operation that will have broad applications. In Hardware, the square root will be designed in order to gain power which will be quite low. Similarly, there are also other advantages that comes with gaining of low power that is high speed and also low area. A trade-off will also occur with the three metrics which is quite natural. As we know that the present technology is very advanced so it will aim for low power and architectural modification will be required by the relative designs. This sheet represents an energy efficient square rooter by using reversible logic. (RCSM) Reversible Controlled Subtract Multiplexer will be designing and it also plays an important part in implementing the binary square rooter. Saimur Rahman Gate will also be implementing the binary square rooter in order to improve and develop it. The Improvements such as cost of the quanta, inputs given by constants and also garbage outputs. The approaches such as conventional approach and SRG are used for designing the binary square rooter and it will be completed using non-restoring algorithm. Xilinx software will be responsible for carrying out simulations and Synopsys Design Compiler will be the factor for obtaining power. The gate count which has been 75 will be decreased to 35. There will be an improvement of 20% in terms of power which will be obtained in this paper.

关键词： Multiplexing Reversible computing Adaptation models VHDL software algorithms Logic gates Energy efficiency

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Scalable Quantitative Verification for Deep Neural Networks

Scalable Quantitative Verification for Deep Neural Networks

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International Conference on software Engineering (ICSE)

作者： Teodora Baluta Zheng Leong Chua Kuldeep S. Meel Prateek Saxena National University of Singapore Independent Researcher

Despite the functional success of deep Neural Networks, their trustworthiness remains a crucial open challenge. To address this challenge, both testing and verification techniques have been proposed. But these existing techniques provide either scalability to large networks or formal guarantees, not both. In this paper, we propose a scalable quantitative verification framework for deep Neural Networks, i.e., a test-driven approach that comes with formal guarantees that a desired probabilistic property is satisfied. Our technique performs enough tests until soundness of a formal probabilistic property can be proven. It can be used to certify properties of both deterministic and randomized DNNs. We implement our approach in a tool called PROVERO and apply it in the context of certifying adversarial robustness of DNNs. In this context, we first show a new attack-agnostic measure of robustness which offers an alternative to purely attack-based methodology of evaluating robustness being reported today. Second, PROVERO provides certificates of robustness for large DNNs, where existing state-of-the-art verification tools fail to produce conclusive results. Our work paves the way forward for verifying properties of distributions captured by real-world deep Neural Networks, with provable guarantees, even where testers only have black-box access to the neural network.

关键词： Neural networks software algorithms Tools Probabilistic logic Robustness Testing software engineering

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