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Incremental one-class learning using regularized null-space training for industrial defect detection
(2024)
One-class incremental learning is a special case of class-incremental learning, where only a single novel class is incrementally added to an existing classifier instead of multiple classes. This case is relevant in industrial defect detection scenarios, where novel defects usually appear during operation. Existing rolled-out classifiers must be updated incrementally in this scenario with only a few novel examples. In addition, it is often required that the base classifier must not be altered due to approval and warranty restrictions. While simple finetuning often gives the best performance across old and new classes, it comes with the drawback of potentially losing performance on the base classes (catastrophic forgetting [1]). Simple prototype approaches [2] work without changing existing weights and perform very well when the classes are well separated but fail dramatically when not. In theory, null-space training (NSCL) [3] should retain the basis classifier entirely, as parameter updates are restricted to the null space of the network with respect to existing classes. However, as we show, this technique promotes overfitting in the case of one-class incremental learning. In our experiments, we found that unconstrained weight growth in null space is the underlying issue, leading us to propose a regularization term (R-NSCL) that penalizes the magnitude of amplification. The regularization term is added to the standard classification loss and stabilizes null-space training in the one-class scenario by counteracting overfitting. We test the method’s capabilities on two industrial datasets, namely AITEX and MVTec, and compare the performance to state-of-the-art algorithms for class-incremental learning.
Using multi-camera matching techniques for 3d reconstruction there is usually the trade-off between the quality of the computed depth map and the speed of the computations. Whereas high quality matching methods take several seconds to several minutes to compute a depth map for one set of images, real-time methods achieve only low quality results. In this paper we present a multi-camera matching method that runs in real-time and yields high resolution depth maps. Our method is based on a novel multi-level combination of normalized cross correlation, deformed matching windows based on the multi-level depth map information, and sub-pixel precise disparity maps. The whole process is implemented completely on the GPU. With this approach we can process four 0.7 megapixel images in 129 milliseconds to a full resolution 3d depth map. Our technique is tailored for the recognition of non-technical shapes, because our target application is face recognition.
This paper broadens the resource-based approach to explaining survival of new technology-based firms (NTBFs) by focusing on the entrepreneur's ability to transform resources in response to triggers resulting from market interactions. Network theory is used to define a construct that allows determining the status of venture emergence (VE).The operationalization of the VE construct is built on the firm's value network maturity in the four market dimensions customer, investor, partner, and human resource. Business plans of NTBFs represent the artifact that contains this data in the form of transaction relation descriptions. Using content analysis, a multi-step combined human and computer coding process has been developed to empirically determine NTBFs' status of VE.Results of the business plan analysis suggests that the level of transaction relations allows to draw conclusions on the status of VE. Moreover, applying the developed process, a business plan coding test shows that the transaction relation based VE status significantly relates to NTBFs' survival capabilities.
Misbehave like Nobody’s Watching? Investor Attention to Corporate Misconduct and its Implications
(2023)
With the advancement in sensor technology and the trend shift of health measurement from treatment after diagnosis to abnormalities detection long before the occurrence, the approach of turning private spaces into diagnostic spaces has gained much attention. In this work, we designed and implemented a low-cost and compact form factor module that can be deployed on the steering wheel of cars as well as most frequently touch objects at home in order to measure physiological signals from the fingertip of the subject as well as environmental parameters. We estimated the heart rate and SpO2 with the error of 2.83 bpm and 3.52%, respectively. The signal evaluation of skin temperature shows a promising output with respect to environmental recalibration. In addition, the electrodermal activity sensor followed the reference signal, appropriately which indicates the potential for further development and application in stress measurement.
The perception of the amount of stress is subjective to every person, and the perception of it changes depending on many factors. One of the factors that has an impact on perceived stress is the emotional state. In this work, we compare the emotional state of 40 German driving students and present different partitions that can be advantageous for using artificial intelligence and classification. Like this, we evaluate the data quality and prepare for the specific use. The Stress Perceived Questionnaire (PSQ20) was employed to assess the level of stress experienced by individuals while participating in a driving simulation for 5 and 25 min. As a result of our analysis, we present a categorisation of various emotional states into intervals, comparing different classifications and facilitating a more straightforward implementation of artificial intelligence for classification purposes.
Evaluation of a Contactless Accelerometer Sensor System for Heart Rate Monitoring During Sleep
(2024)
The monitoring of a patient's heart rate (HR) is critical in the diagnosis of diseases. In the detection of sleep disorders, it also plays an important role. Several techniques have been proposed, including using sensors to record physiological signals that are automatically examined and analysed. This work aims to evaluate using a contactless HR monitoring system based on an accelerometer sensor during sleep. For this purpose, the oscillations caused by chest movements during heart contractions are recorded by an installation mounted under the bed mattress. The processing algorithm presented in this paper filters the signals and determines the HR. As a result, an average error of about 5 bpm has been documented, i.e., the system can be considered to be used for the forecasted domain.
In the digital age, information technology (IT) is a strategic asset for organizations. As a result, the IT costs are rising, and the cost-effective management of IT is crucial. Nevertheless, organizations still face major challenges and former studies lack comprehensiveness and depth. The goal of this paper is to generate a deep and holistic view on current management challenges of IT costs. In 15 expert interviews, we identify 23 challenges divided into 7 categories. The main challenges are to ensure transparency on IT cost information, to demonstrate the business impact of IT as well as to change the mindset for the value of IT and overcoming them requires attention to their interactions. Hence, this paper leads to a better understanding of the issues that IT cost management (ITCM) faces in the digital age and builds a base for future research.
Nowadays, organizations must invest strategically in information technology (IT) and choose the right digital initiatives to maximize their benefit. Nevertheless, Chief Information Officers still struggle to communicate IT costs and demonstrate the business value of IT. The goal of this paper is to support their effective communication. In focus groups, we analyzed how different stakeholders perceive IT costs and the business value of IT as the basis of communication. We identified 16 success factors to establish effective communication. Hence, this paper enables a better understanding of the perception and the operationalization of effective communication.
Prior quantitative research identified in the text of technology-based ventures' business plans distinctive performance patterns of evolving business models. Accordingly, interactions with customers, financiers, and people and the patenting strategy's status evolved and served as indicators of early-stage tech ventures' performance. With longitudinal data from five venture cases, this research sheds light on the evolving business model by validating the performance patterns, and elucidating how and why the ventures' business models evolved. Based on a generic systems theory framework for the indicators, the explanatory case studies re-contextualize the performance patterns taken from the snapshot perspective of business plans to the longitudinal perspective of technology-based ventures' life-cycle. This research confirms the relation of business model patterns of digital and non-digital ventures to the performance groups of failure, survival, or success and suggests a broader systems perspective for further research.
The digital transformation of business processes and the integration of IT systems leads to opportunities and risks for small and medium-sized enterprises (SMEs). Risks that can result in a lack of IT Governance, Risk and Compliance (GRC). The purpose of this paper is to present the Design and Evaluation phase of creating an artefact, to reduce these risks. With this, the Design Science Research approach based on Hevner is using. The artefact will be developed by selecting relevant existing frameworks and the identification of SME-specific competencies. The method enables IT-GRC managers to transfer or adapt the frameworks to an SME organizational structure. The results from ten interviews and further three feedback loops showed that the method can be applied in practice and that a tailoring of established frameworks can take place. Contrary to the previous basic orientation of the research, this paper focuses on the concretization of approaches.
The random matrix approach is a robust algorithm to filter the mean and covariance matrix of noisy observations of a dynamic object. Afterward, virtual measurement models can be used to find iteratively the extent parameters of an object that would cause the same statistical moments within their measurements. In previous work, this was limited to elliptical targets and only contour measurements.In this paper, we introduce the parallel use of an elliptical, triangular and rectangular-shaped virtual measurement model and a shape classification that selects the model that fits best to the measurements. The measurement likelihood is modeled either via ray tracing, a uniformly or normally spatial distribution over the object’s extent or as a combination of those.The results show that the extent estimation works precisely and that the classification accuracy highly depends on the measurement noise.
Regional economies clearly benefit from thriving entrepreneurial ecosystems. However, ecosystems are not yet entirely gender-inclusive and therefore are not tapping their full potential. This is most critical with respect to technology-based entrepreneurship which features the largest gender imbalance. Despite the considerably growing amount of literature in the two research fields of female entrepreneurship and entrepreneurial ecosystems, the intersection of the two areas has not yet been outlined. We depict the state of knowledge with a structured review of the literature highlighting bibliometric information, methods used, and the main topics addressed in current articles. From there, recommendations for future research are derived.
Think BIQ: Gender Differences, Entrepreneurship Support and the Quality of Business Idea Description
(2023)
Entrepreneurship support, its influencing factors and female entrepreneurship are recently discussed topics with great relevance for society and politics. However, research on the subject has been divergent in its results and lacks a focus on the impact of support programs’ characteristics concerning different types of entrepreneurs. Thus, we conduct a fuzzy-set Qualitative Comparative Analysis on entrepreneurship support characteristics aiming to shed light on possible gender differences occurring in respective programs. We investigate the quality of business idea descriptions, as a predecessor for a high-potential business model, operationalized using inter alia causation and effectuation theory and social role theory as possible explanations. In our fuzzy-set Qualitative Comparative Analysis on a sample of 911 Norwegian ventures, we find a variety of differences related to the entrepreneurs’ gender. For instance, that financial support combined with a well described key contribution or careful planning seem to be more important antecedents for female entrepreneurs’ business idea quality than for males. Moreover, it seems a well-described key contribution has a positive effect on the outcome variable in most cases. Another interesting finding concerns the entrepreneurs’ network partners, where we found evident gender differences in our combinations. Female entrepreneurs seemingly benefitted from rather small networks, and males from big networks, although the former possess larger networks in the sample. In conclusion, we find that gender differences in combinations of entrepreneurship support for high business idea quality still occur even in a country like Norway, calling for an adaption of the provided support and environment.
Strategic renewal and the development of new types of innovation pose special challenges to established small and medium-sized companies. The paper at hand aims at answering the questions what the underlying mechanism of these challenges are and which approaches might help to properly counteracting them. This case study investigates the strategic renewal process and its corresponding interventions in a high-tech SME company during a four-year period. We analyse the findings in relation to existing frameworks for dynamic capabilities and strategic learning and provide new recommendations for practice and future research.
Research credits corporate entrepreneurship (CE) with enabling established companies to create new types of innovation. Scholars have focused on the organizational design of CE activities, proposing specific organizational units. These semi-autonomous units create a tense management situation between the core organization and its CE activities. Management and organization research considers control as a key managerial function for help. However, control has received limited research attention regarding CE units, leaving design issues for appropriate control of CE units unanswered. In this study, we link management control and CE to illustrate how control is understood in the context of CE. For this, we scanned the CE literature to identify underlying attributes and characteristics that allow specifying control for CE. We identified 11 attributes to describe control for CE activities in a first round and to derive future research paths.
Corporate Entrepreneurship (CE) units have become an increasingly important part of established companies’ development activities enabling them to also create more discontinuous innovations. As a result, companies have developed and implemented different forms of CE units, such as corporate accelerators, incubators, startup supplier programs, and corporate venture capital. Driven by the need to innovate, companies have even begun to use multiple CE units simultaneously. However, this has not been empirically investigated yet. Thus, with this study, we aim to shed some light on this by investigating the parallel use of multiple CE units in the German business landscape. We conducted an extensive desk research, combining, coding, and analyzing different sources. We found that 55 out of 165 large established companies have multiple CE units, which allowed us to characterize the parallel use and identify differences and similarities, e.g., in terms of industry, company size, and CE forms implemented. We conclude by presenting different implications for both practice and research and by pointing out directions for future research.
Spatial modulation (SM) is a low-complexity multiple-input/multiple-output transmission technique that combines index modulation and quadrature amplitude modulation for wireless communications. In this work, we consider the problem of link adaption for generalized spatial modulation (GSM) systems that use multiple active transmit antennas simultaneously. Link adaption algorithms require a real-time estimation of the link quality of the time-variant communication channels, e.g., by means of estimating the mutual information. However, determining the mutual information of SM is challenging because no closed-form expressions have been found so far. Recently, multilayer feedforward neural networks were applied to compute the achievable rate of an index modulation link. However, only a small SM system with two transmit and two receive antennas was considered. In this work, we consider a similar approach but investigate larger GSM systems with multiple active antennas. We analyze the portions of mutual information related to antenna selection and the IQ modulation processes, which depend on the GSM variant and the signal constellation.