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MA-MFIF: When misaligned multi-focus Image fusion meets deep homography estimation

Multimedia Tools and Applications 2025年第12期84卷 10877-10898页

作者： Zhao, Baojun Luo, Fei Fuentes, Joel Ding, Weichao Gu, Chunhua School of Information Science and Engineering East China University of Science and Technology Shanghai200237 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China Department of Computer Science and Information Technologies Universidad del Bio-Bio Chillán3780000 Chile

Multi-focus image fusion is a technique that combines multiple out-of-focus images to enhance the overall image quality. It has gained significant attention in recent years, thanks to the advancements in deep learning. However, one of the persistent challenges in this field is the processing of misaligned data, which can negatively impact the fusion results. To overcome this problem, a novel fusion framework with pre-registration is proposed for the fusion of misaligned multi-focus images. For pre-registration, content-aware deep homography estimation is used, which performs transfer learning on a real multi-focus image dataset to adapt to registration under defocused conditions. For fusion, a fusion module with dual-branch feature interaction is utilized to avoid invalid feature fusion and trained on real light field dataset to achieve better fusion performance. Qualitative and quantitative experimental results show that the proposed method has a 2-3 percentage point improvement in multiple evaluation metrics compared to existing advanced registration and fusion methods, and a maximum improvement of 4.83 percentage points in fusion performance when tested independently on the Lytro dataset. Additionally, We find that the value of the Qcv metric is greatly influenced by the alignment status of the input images, leading to its inability to reflect the fusion quality of aligned images. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Image enhancement

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InsightCube: Accelerating Interactive Insight Discovery in Exploratory Data Analysis

InsightCube: Accelerating Interactive Insight Discovery in E...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Hanbing Zhang Yinan Jing Wei Zhang Zhenying He Kai Zhang X. Sean Wang Zhenqiang Chen Changchun Zhang School of Computer Science Fudan University Shanghai China Shanghai Key Laboratory of Data Science Shanghai China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China Transwarp Technology(Shanghai) Co. Ltd Shanghai China

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

Exploratory data analysis (EDA) is usually human-in-the-loop and time tedious since identifying insights that show interesting characteristics and trends in data is laborious. Insight discovery helps users gain structured knowledge when understanding the dataset by categorizing interesting characteristics and trends into commonnesses and exceptions. However, existing insight discovery methods cannot interact with users when discovering insights. More importantly, the efficiency of insight discovery for these methods is low. In this paper, we propose a framework that supports and accelerates interactive insight discovery. We first divide the dataset into multiple subsets, and precompute the pattern snippets that include the distribution characteristics of subsets. Considering efficiency, we only pre-compute for subsets that cannot be further split. Then we design a novel cube structure, called InsightCube, to store precomputed pattern snippets. In order to accelerate insight discovery, we reuse the precomputed pattern snippets stored in InsightCube to infer the pattern of subsets that cannot be split. Furthermore, during insight discovery, we propose pruning strategies to accelerate the pattern inference for subsets that can be split. Experimental results on real-world datasets show that InsightCube improves the insight discovery efficiency by up to $2.5 \times$ compared to the state-of-the-art insight discovery method.

关键词： Data analysis Big Data Market research Human in the loop Optimization

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Practical Strategies to Improve Test Efficiency

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Tsinghua Science and Technology 2007年第S1期12卷 250-254页

作者：丁志刚汪泓澄凌良合 Shanghai Development Center of Software Technology Shanghai Key Laboratory of Computer Software Evaluating and Testing

This paper introduces strategies to detect software bugs in earlier life cycle stage in order to improve test efficiency. Static analysis tool is one of the effective methods to reveal software bugs during software development. Three popular static analysis tools are introduced, two of which, PolySpace and Splint, are compared with each other by analyzing a set of test cases generatedd by the authors. PolySpace can reveal 60% bugs with 100% R/W ratio (ratio of real bugs and total warnings), while Splint reveal 73.3% bugs with 44% R/W ratio. And they are good at finding different categories of bugs. Two strategies are concluded to improve test efficiency, under the guideline that static analysis tools should be used in finding different categories of bugs according to their features. The first one aims at finding bugs as many as possible, while the second concentrates to reduce the average time on bug revelation. Experimental data shows the first strategy can find 100% bugs with 60% R/W ratio, the second one find 80% bugs with 66.7% R/W ratio. Experiment results prove that these two strategies can improve the test efficiency in both fault coverage and testing time.

关键词： static analysis PolySpace splint software bug

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software Test Case Generation with Adequacy Analysis on Scenario-Based testing

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Journal of Donghua University(English Edition) 2011年第2期28卷 139-144页

作者：刘振宇杨根兴蔡立志 School of Computer Science Fudan University Shanghai Key Laboratory of Computer Software Evaluating and Testing

This paper studies the software scenario testing, which is commonly used in black-box testing at present. In the paper, the workflow model based on task-driven, which is very common in scenario testing, is analyzed. According to test adequacy criteria in scenario testing, the model is designed to correspond test cases in the light of logic block(LB). The final test cases that conform to the test adequacy criteria can be obtained through test case combination and test case reduction. In the last part of the paper, example of actual workflow is to design the efficient test case. Therefore the method is proved to be effective.

关键词： test case test adequacy system scenario software testing

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PSO-Based Black-Box Lane Detection Adversarial Attack 2

PSO-Based Black-Box Lane Detection Adversarial Attack

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2nd International Conference on Artificial Intelligence, Human-computer Interaction and Robotics, AIHCIR 2023

作者： Fang, Hongtao Wang, Ruiyun Ma, Zeyu Chen, Mingang Shanghai Polytechnic University Shanghai Key Laboratory of Computer Software Testing and Evaluating shanghai China Shanghai Normal University Shanghai Key Laboratory of Computer Software Testing and Evaluating shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating shanghai China

ISBN: (纸本)9798350360363

Autonomous driving has achieved rapid development and promising performance by employing machine learning algorithms to automatically execute various maneuvers. Lane detection is one of the foremost tasks for vehicles, with a direct impact on driving decisions. Lane detection is a crucial component of autonomous driving, working in conjunction with lane centering control (LCC) and adaptive cruise control (ACC) to enable advanced driving assistance functions. At first thought, lane detection may seem immune to attacks. However, is this really the case? In this paper, we conduct experiments on lane detection modules and reveal their susceptibility to attacks exploiting hypersensitivity. Specifically, an excessively sensitive lane detector may mistake small markings for valid lanes, causing the vehicle to follow the wrong path. Through experiments, we demonstrate the vulnerability of lane detection models to adversarial attacks, even under black-box conditions where a change in one pixel can induce errors. We discuss the contrast between gradient-based and heuristic search-based optimization methods for black-box attacks and demonstrate the superiority of heuristic approaches for this task. Leveraging particle swarm optimization (PSO), we carry out lane detection attacks to address the research gap for black-box lane attacks. © 2023 IEEE.

关键词： Autonomous vehicles

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Testability metrics for software behavioral models

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International Journal of Performability Engineering 2017年第8期13卷 1171-1182页

作者： Liu, Pan College of Information and Computer Shanghai Business School Shanghai201400 China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai201112 China

Design for testability is one of the important research interests in software engineering. It becomes crucial in model-based testing because software behavioral models can be used to construct test sequences to perform conformance testing. However, testability of models has received less attention in the past. A model with high testability is easy to be used to construct effective test sequences, and conformance testing can also be realized easily. To improve testability of software behavioral models, using the formal method, we present five testability metrics: observability, controllability, test constructibility, performability, and error traceability. Then, a case is studied to evaluate the effectiveness of proposed testability metrics. As a result of the case study, models with higher testability can not only be used to generate executable test sequences, but also the size of the constructed test suite is also smaller. Our research will enrich the modeling theory of model-based testing and can improve the application of this test method in industry. © 2017 Totem Publisher, Inc. All rights reserved.

关键词： Behavioral research

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The Web Application Test Based on Page Coverage Criteria

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Journal of Donghua University(English Edition) 2008年第3期25卷 291-296页

作者：蔡立志童维勤杨根兴 School of Computer Engineering and Science Shanghai University The Key Lab of Software Testing and Evaluating

software testing coverage criteria play an important role in the whole testing *** current coverage criteria for web applications are based on program or *** are not suitable for black-box test or intuitional to *** paper defines a kind of test criteria based on page coverage sequences only navigated by web application,including Page_Single,Page_Post,Page_Pre,Page_Seq2,Page_*** test criteria based on page coverage sequences made by interactions between web application and browser are being under consideration after *** order to avoid ambiguity of natural language,these coverage criteria are depicted using Z formal *** empirical result shows that the criteria complement traditional coverage and fault detection capability criteria.

关键词： web application coverage criteria browser interaction Z formal language

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Towards common acquaintance immunization strategy for complex network

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Information Technology Journal 2009年第8期8卷 1129-1139页

作者： Liu, Pan Miao, Huaikou Mei, Jia School of Computer Engineer and Science Shanghai University Shanghai 200072 China Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai 201112 China

The study presents a new immunization strategy for computer networks and populations with board and, in particular, scale-free degree distributions. The proposed strategy calls for the immunization of common acquaintances of random nodes (individuals). Similar to acquaintance immunization, our strategy also requires no knowledge of the node degrees or any other global information. Firstly, we analyze the successful and unsuccessful probability of acquaintance immunization with a simple example and the strategy ineffective reasons. Then, we study the probability of looking for common neighbors and present common acquaintance immunization strategy. Next, to compare common acquaintance immunization with acquaintance immunization, we implement a series of experiments from different aspects. The result of experiments shows that common acquaintance immunization gains higher stability and reliability for protecting complex network and can detect the structure of the unknown network. The conclusions of the study are that, compared with other immunization strategy, our approach requires no the whole information of complex network and efficiently immunizes the HUBS in complex network. © 2009 Asian Network for Scientific Information.

关键词： Complex networks

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Application and method of quality management for small-size software project

Application and method of quality management for small-size ...

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IET International Conference on Information Science and Control Engineering 2012, ICISCE 2012

作者： Yang, Lin Liu, Zhenyu Cai, Lizhi Shanghai Key Laboratory of Computer Software Evaluating and Testing Shanghai China

ISBN: (纸本)9781849196413

This paper studies the quality management method in small-size software project. In traditional method, test and evaluation are prerequisite methods to improve the project quality. The paper analyses characteristics and the disadvantages of project management in small-sized software project. Therefore, some quality activities should be considered in small-sized software project. The paper proposed lightweight quality planning, quality execution and quality monitoring activities in project management. Finally, the paper gives practical applications and proves method effective.

关键词： software testing

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Performance evaluation of recommender systems

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International Journal of Performability Engineering 2017年第8期13卷 1246-1256页

作者： Chen, Mingang Liu, Pan Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai201112 China Shanghai Development Center of Computer Software Technology Shanghai201112 China Shanghai Business School Shanghai201112 China

Recommender systems play an important role in e-commerce. This paper discusses three classical methods-offline analytics, user study, and online experiment-to evaluate the performance of recommender systems and also analyzes their application scenarios. Some performance evaluation metrics of recommender systems are reviewed and summarized from four perspectives (machine learning, information retrieval, human-computer interaction and software engineering) combined with the above three evaluation methods. These evaluation methods and evaluation metrics summarized in the paper provide the designers with guidance for the comprehensive evaluation and selection of recommended algorithms. © 2017 Totem Publisher, Inc. All rights reserved.

关键词： Recommender systems

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