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检索条件"任意字段=6th International Conference on the Art, Science, and Engineering of Programming, Programming 2022"

共 1076 条记录，以下是511-520 订阅

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Cross-Modal Relation and Sketch Prototype Learning for Zero-Shot Sketch-Based Image Retrieval 22

Cross-Modal Relation and Sketch Prototype Learning for Zero-...

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Proceedings of the 2022 6th international conference on Computer science and artificial Intelligence

作者： Yuanping Song Yanwei Yu Hao Tang Junyuan Guo Yibo Wang School of Software Engineering University Of Science And Technology Of China China School of Software Engineering Suzhou Institute for Advanced Research University Of Science And Technology Of China China

ISBN: (纸本)9781450397773

Zero-Shot Sketch-Based Image Retrieval (ZS-SBIR) is an innovative cross-modal task that utilizes a sketch to retrieve corresponding images in the zero-shot learning scene. At present, most algorithms treat ZS-SBIR as a typical image classification problem, using image-level features with triplet or cross entropy loss to achieve retrieval, while ignore the correspondence between sketches and images on local features. therefore, we propose a new Local Feature Contrastive Network (LFCN) for ZS-SBIR from the perspective of contrastive learning. More specifically, a local feature contrastive method is proposed to establish the cross-modal relationships between images and sketches with creatively applying transformers to extract similarity representation from sketch-image pairs to narrow the domain gap. Furthermore, a feature prototype memory bank is designed to learn sketch prototypes to address the in-class diversity problem in sketch domain. A large number of experiments show that our method notably superior to the state-of-the-art algorithms in both TU-Berlin and Sketchy datasets.

关键词： local features reranking transformer contrastive learning sketch-based image retrieval

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Generative Cooperative Network for Person Image Generation

Generative Cooperative Network for Person Image Generation

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international conference on Universal Village (UV)

作者： Yang Liu Shuai Wang Yubin Wu Hao Sheng Zhang Xiong State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China

Person image generation is to synthesize realistic pedestrian images that follow the same distribution as the given dataset. Previous attempts can be generally categorized into two classes: some methods use human pose information as guidance and others try to generate person images from scratch. the former is to transfer the pose of a source image to a reference pose. the generated person image have the same identity as the source image. the latter takes a random noise from latent space as input, and the real person images are only used as references for the discriminator. While pose-guided person image generation is widely studied, generating-from-scratch methods are also worth exploring because they can synthesize person image with new identity, which is a useful manner of data augmentation. these two types of generating methods have their different advantages and disadvantages, and sometimes they are complementary. In this work, the authors design a Generative Cooperative Network (GCN) to jointly train two types of GANs. the two GANs serve different purposes, and can learn from each other during the cooperative learning procedure. the proposed approach is verified on public datasets, and the results show that our GCN improves the performance of the baseline methods. Comparisons with state-of-the-art methods also prove the effectiveness of the proposed method.

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Proceedings - 2018 6th international conference on Learning and Teaching in Computing and engineering, LaTiCE 2018

Proceedings - 2018 6th International Conference on Learning ...

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6th international conference on Learning and Teaching in Computing and engineering, LaTiCE 2018

ISBN: (纸本)9781538678978

the proceedings contain 25 papers. the topics discussed include: active learning for out-of-class activities by using interactive mobile apps;social constructivism learning through project based learning with scaffolding in flipped classroom;flipped classroom strategy to help underachievers in java programming;knowledge sequencing in online courses for introductory programming;an activity theory framework to explore social media and nostalgia as coping tools for international students;development and validation of problem solving task based-integrated STEM;the use of different kinds of robots to spark student interest in learning computational thinking;culturally relevant approach to encourage school children learn computer science concepts: using game based education strategy for student learning effectiveness and motivation;and designing an augmented reality application to learn three-dimensional views.

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Using AIG in Verilog HDL, Autonomous Testing in a Family of Wien Bridge Cross Transducers

Using AIG in Verilog HDL, Autonomous Testing in a Family of ...

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international conference on Contemporary Computing and Informatics (IC3I)

作者： K N Raja Praveen Gadug Sudhamsu Department of Computer Science and Engineering Faculty of Engineering and Technology Jain (Deemed-to-be University) Bangalore Karnataka India

this research reports on the software configuration of automated fault detection and recognition using neural networks (ANNs) in a class of 13.6 cross actuators. According to the findings, the suggested flaw detector is ideal for integrating knowledge into the devices in a way that is living thing. the seven often recurring defects in a batch of these sensors are directly determined by the automated fault tester that is being demonstrated. In this study, the suggested automated defect detector is trained using an ANN-based binary class system. If any of the mistakes occurs, logic programming is applied to define a high or ”1” output, whereas the returning is calculated whether the other 6 failures occurred lowest or ”0”. the input outputs from the Or CAD programme are used as incoming signal, and indeed the produced train parameters, i.e., amplitude and biased of the artificial neural tool of Math, have been used.

关键词： Fault diagnosis Actuators Transducers Software packages Bridge circuits Detectors Sensors

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Out of Distribution Reasoning by Weakly-Supervised Disentangled Logic Variational Autoencoder

Out of Distribution Reasoning by Weakly-Supervised Disentang...

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international conference on System Reliability and science (ICSRS)

作者： Zahra Rahiminasab Michael Yuhas Arvind Easwaran School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Energy Research Institute Nanyang Technological University Singapore Singapore

Out-of-distribution (OOD) detection, i.e., finding test samples derived from a different distribution than the training set, as well as reasoning about such samples (OOD reasoning), are necessary to ensure the safety of results generated by machine learning models. Recently there have been promising results for OOD detection in the latent space of variational autoencoders (VAEs). However, without disentanglement, VAEs cannot perform OOD reasoning. Disentanglement ensures a one-to-many mapping between generative factors of OOD (e.g., rain in image data) and the latent variables to which they are encoded. Although previous literature has focused on weakly-supervised disentanglement on simple datasets with known and independent generative factors. In practice, achieving full disentanglement through weak supervision is impossible for complex datasets, such as Carla, with unknown and abstract generative factors. As a result, we propose an OOD reasoning framework that learns a partially disentangled VAE to reason about complex datasets. Our framework consists of three steps: partitioning data based on observed generative factors, training a VAE as a logic tensor network that satisfies disentanglement rules, and run-time OOD reasoning. We evaluate our approach on the Carla dataset and compare the results against three state-of-the-art methods. We found that our framework outperformed these methods in terms of disentanglement and end-to-end OOD reasoning.

关键词： Training Rain Tensors three-dimensional displays Urban areas Machine learning Cognition

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Decision-based adversarial attack for speaker recognition models 22

Decision-based adversarial attack for speaker recognition mo...

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Proceedings of the 2022 6th international conference on Computer science and artificial Intelligence

作者： Xueyang Cao Shanshan Wang Zhenxiang Chen Xiaoqing Jiang Weiliang Zheng Yadi Han School of Information Science and Engineering University of Jinan China China

ISBN: (纸本)9781450397773

As a biometric technology, speaker recognition is widely used in finance, criminal investigation, and other fields due to its convenience and high accuracy. Speaker recognition models are vulnerable to spoofing attacks and adversarial attacks. thus, the security of speaker recognition models has received much attention. However, few works focus on the decision-based adversarial attacks for speaker recognition systems (SRS), in which the adversary can only access the final decisions of the black-box models. In this paper, we proposed Biased-Aha, a decision-based attack method that combined query history information and prior gradient from the substitution model to launch an efficient attack. Specifically, to generate the adversarial example, the perturbation is determined by following the sampling direction for successful queries and avoiding the sampling direction for failed queries, combined with the gradient direction from the substitution model. the experiment results show that Biased-Aha takes a high attack success rate and high efficiency. For the speaker recognition models, Gaussian Mixture Models (GMM) and ivector, Biased-Aha outperforms the state-of-the-art decision-based adversarial attacks.

关键词： Black-box Speaker recognition Decision-based adversarial attack Substitution model

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Weather Station Using Raspberry Pi 6

Weather Station Using Raspberry Pi

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6th international conference on Image Information Processing, ICIIP 2021

作者： Mathur, Vivek Saini, Yashika Giri, Vipul Choudhary, Vikas Bharadwaj, Uday Kumar, Vishal Aiet Department of Computer Science and Engineering Jaipur India

ISBN: (纸本)9781665433617

Weather is the everyday climate that is hard to predict and impacts human activities and is important in many different sectors. However, it is expensive and huge, bringing pain to current meteorological stations on the market. the aim is to develop a weather station that provides real-Time warnings for climate monitoring, interfaces with a cloud platform and analyses weather. this project has been completed with a Weather Station to record weather conditions by means of SparkFun Weather Shield, Arduino Uno R3 and Weather Meter. Data from the sensors are then recorded using Raspberry Pi 3 Model B in Google Cloud SQL, where they are gateway and the analysis of meteorological data is done. the website and mobile application are designed to illustrate real-Time weather conditions for managing and users using Google Data Studio and Android Studio. In this article various environmental components may be monitored in real time utilising IoT at minimum costs. For this reason, we use the ARM-based Raspberry Pi board. the Raspberry Pi OS is selected for the Linux kernel. Python, as the Idle is understood, is a programming language. A wide range of digital and analogue sensors, such DHT11, BMP180, LDR and a distinctive scale, are used with ULN2803 for measuring the environment parameter. the Raspberry Pi server, which is saved to CSV and text files, reads these input sensor data. Customers may obtain this information from anywhere in the globe on *** in real time. To connect the server to the client, use the HTTP protocol. © 2021 IEEE.

关键词： HTTP

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A Deployment Method Based on artificial Bee Colony Algorithm for UAV-Mounted Base Stations 1

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6th EAI international conference on IoT as a Service, IoTaaS 2020

作者： Zhang, Chen Zhang, Leyi Liu, Yanming Zhu, Lipeng Xiao, Zhenyu School of Electronic and Information Engineering Beihang University Beijing100191 China

ISBN: (数字)9783030675141

ISBN: (纸本)9783030675134

With high mobility and low cost, unmanned aerial vehicles (UAVs) are widely used in wireless communication systems. Especially in emergencies, UAVs can be used as aerial base stations (BSs) to provide wireless communication services for ground users. Aiming to reduce cost, we prefer to minimizing the number of UAVs needed to serve all users. Compared with the existing works, we take the constraints of required quality of service (QoS) and the service ability of each UAV into consideration. To solve the formulated mixed-integer programming problem, we propose a three-step method. First, to ensure each UAV can serve more users, the maximum service radius of UAVs is derived according to users’ QoS requirement. Second, we propose an artificial bee colony (ABC) algorithm based clustering method to cluster users into different groups in the horizontal direction. third, we adjust the positions of UAVs to obtained a better communication performance of the wireless communication system. Finally, the simulation results are presented to demonstrate the superiority of the proposed method. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications engineering.

关键词： Base stations

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GPTE: Efficient Graph Partitioning-based Traffic engineering in Hybrid SDN/IP Networks 22

GPTE: Efficient Graph Partitioning-based Traffic Engineering...

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22nd IEEE international conference on High Performance Computing and Communications, 18th IEEE international conference on Smart City and 6th IEEE international conference on Data science and Systems, HPCC-SmartCity-DSS 2020

作者： Dai, Huijun Zhu, Min Wang, Li Zhao, Jianlong Gui, Xiaolin Peng, Guangyu Shanxi Province Key Laboratory of Computer Network Xi'an Jiaotong Univercity School of Computer Science Shanxi Xi'an China Xi'an Jiaotong Univercity School of Communication Engineering Shanxi Xi'an China Huawei Company Shanxi Xi'an China Qingdao Hisense TransTech Co Ltd Shandong Qingdao China Xi'an Jiaotong Univercity School of Computer Science Shanxi Xi'an China

ISBN: (纸本)9781728176499

Due to the lack of a centralized global view on the Traditional IP network, it may cause load imbalance or network congestion. Because of the high economical costs and technical conditions of the migration to full SDN, network operators prefer partial deployment of SDN-enabled devices in the IP network. An efficient graph partitioning-based TE (GPTE) in hybrid SDN/IP networks is proposed by considering the network topology, in which legacy devices and SDN-enabled devices co-exist. Firstly, GPTE models the partial SDN deployment as a Network Partitioning Problem solved by transforming the original network into its dual, which make the representation applicable to partitioning. Afterwards, GPTE formulates the TE as an Integer Linear programming (ILP) by considering hybrid SDN/IP routing mechanism. Finally, through intensive experiments under different topologies, GPTE can achieve a significant improvements in terms of load balancing performance and can provide better TE capabilities. © 2020 IEEE.

关键词： Integer programming

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Energy Efficient Resource Allocation for Time Switching Wireless Powered NOMA Networks 6

Energy Efficient Resource Allocation for Time Switching Wire...

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6th IEEE international conference on Computer and Communications, ICCC 2020

作者： Cao, Chengyu Zhao, Jian School of Electronic Science and Engineering Nanjing University Nanjing210023 China

ISBN: (纸本)9781728186351

Non-orthogonal multiple access (NOMA) has attracted much attention from not only industry but also academia and has the potential to meet the demand of increasing data rate. In this paper, the problem of joint resource allocation and time switching (TS) control in wireless-powered NOMA internet of things (IoT) network is considered. We aim to maximize the sum of user-centric energy efficiency (EE) in the system. the optimization problem is divided into subcarrier allocation, power control and TS control. Firstly, the subcarrier allocation problem is a mixed-integer non-linear programming problem which is non-convex. thus two-sided matching algorithm is proposed to optimize subcarrier allocation with low complexity. then because the sum of user-centric EE is the sum of fractional programming problem, successive convex approximation (SCA) is applied to solve the problem. Finally, the simulation results show convergence of the proposed optimization scheme and we achieve better performance than orthogonal frequency division multiple access (OFDMA) scheme. © 2020 IEEE.

关键词： Energy efficiency

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