15 research outputs found
Methods for Understanding and Improving Deep Learning Classification Models
Recently proposed deep learning systems can achieve superior performance with respect to methods based on hand-crafted features on a broad range of tasks, not limited to the object recognition/detection tasks, but also on medical image analysis and game control applications. These advances can be credited in part to the rapid development of computation hardware, and the availability of large-scale public datasets. The training process of deep learning models is a challenging task because of the large number of parameters involved, which requires large annotated training sets. A number of recent works have tried to explain the behaviour of deep learning models during training and testing, but the whole field still has limited understanding of the functionality of deep learning models. In this thesis, we aim to develop methods that allow for a better understanding of the behaviour of deep learning models. With such methods, we attempt to improve the performance of deep learning models in several applications and reveal promising directions to explore with empirical evidence. Our first method is a novel nonlinear hierarchical classifier that uses off-the-shelf convolutional neural network (CNN) features. This nonlinear classifier is a tree-structured classifier that uses linear classifier as tree nodes. Experiments suggest that our proposed nonlinear hierarchical classifier achieves better results than the linear classifiers. In our second method, we use Maxout activation function to replace the common rectified linear unit (ReLU) function to increase the model capacity of deep learning models. We found that it can lead to an ill-conditioned training problem, given that the input data is generally not properly normalised. We show how to mitigate this problem by incorporating Batch Normalisation. This method allows us to build a deep learning model that surpassed the performance of several state-of-the-art methods. In the third method, we explore the possibility of introducing multiple-size features into deep learning models. Our design includes up to four different filter sizes to provide different spatial pattern candidates, and a max pooling function that selects the maximum response to represent the unitâs output. As an outcome of this work, we combine the multiple-size filters and the Batch-normalised Maxout activation unit from the second work to achieve the automatic spatial pattern selection within the activation unit. The result of this research shows significant improvements over the state-of-the-art on five publicly available computer vision datasets, including the ImageNet 2012 dataset. Finally, we propose two novel measurements derived from the eigenvalues of the approximate empirical Fisher matrix which can be efficiently calculated within the stochastic gradient descent (SGD) iteration. These measurements can be obtained efficiently even for the recent state-of-the-art deep residual networks. We show how to use these measurements to help select training hyper-parameters such as mini-batch size, model structure, learning rate and stochastic depth rate. By using these tools, we discover a new way to schedule the dynamic sampling and dynamic stochastic depth, which leads to performance improvements of deep learning models. We show the proposed training approach reaches competitive classification results in CIFAR-10 and CIFAR- 100 datasets with models that have significantly lower capacity compare to the current state-of-the-art in the field.Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 201
The use of deep learning features in a hierarchical classifier learned with the minimization of a non-greedy loss function that delays gratification
Recently, we have observed the traditional feature representations are being rapidly replaced by the deep learning representations, which produce significantly more accurate classification results when used together with the linear classifiers. However, it is widely known that non-linear classifiers can generally provide more accurate classification but at a higher computational cost involved in their training and testing procedures. In this paper, we propose a new efficient and accurate non-linear hierarchical classification method that uses the aforementioned deep learning representations. In essence, our classifier is based on a binary tree, where each node is represented by a linear classifier trained using a loss function that minimizes the classification error in a non-greedy way, in addition to postponing hard classification problems to further down the tree. In comparison with linear classifiers, our training process increases only marginally the training and testing time complexities, while showing competitive classification accuracy results. In addition, our method is shown to generalize better than shallow non-linear classifiers. Empirical validation shows that the proposed classifier produces more accurate classification results when compared to several linear and non-linear classifiers on Pascal VOC07 database.Zhibin Liao and Gustavo Carneir
Artificial general intelligence: Proceedings of the Second Conference on Artificial General Intelligence, AGI 2009, Arlington, Virginia, USA, March 6-9, 2009
Artificial General Intelligence (AGI) research focuses on the original and ultimate goal of AI â to create broad human-like and transhuman intelligence, by exploring all available paths, including theoretical and experimental computer science, cognitive science, neuroscience, and innovative interdisciplinary methodologies. Due to the difficulty of this task, for the last few decades the majority of AI researchers have focused on what has been called narrow AI â the production of AI systems displaying intelligence regarding specific, highly constrained tasks. In
recent years, however, more and more researchers have recognized the necessity â and feasibility â of returning to the original goals of the field. Increasingly, there is a call for a transition back to confronting the more difficult issues of human level intelligence and more broadly artificial general intelligence
Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband
Erschienen bei: universi - UniversitÀtsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt:
Track 1: Produktion & Cyber-Physische Systeme
Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities
Service Systems, Smart Service Systems and Cyber- Physical SystemsâWhatâs the difference? Towards a Unified Terminology
Developing an Industrial IoT Platform â Trade-off between Horizontal and Vertical Approaches
Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory
Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case
Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie
Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis
Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs
Track 2: Logistic Analytics
An Empirical Study of Customersâ Behavioral Intention to Use Ridepooling Services â An Extension of the Technology Acceptance Model
Modeling Delay Propagation and Transmission in Railway Networks
What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards?
Robust Route Planning in Intermodal Urban Traffic
Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design)
Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes
Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement
Strategic Analysis in the Realm of Enterprise Modeling â On the Example of Blockchain-Based Initiatives for the Electricity Sector
Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren
Novicesâ Quality Perceptions and the Acceptance of Process Modeling Grammars
Entwicklung einer Definition fĂŒr Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen
Designing a Reference Model for Digital Product Configurators
Terminology for Evolving Design Artifacts
Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects
Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications
Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy
Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications
Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management)
eGovernment Competences revisited â A Literature Review on necessary Competences in a Digitalized Public Sector
Say Hello to Your New Automated Tutor â A Structured Literature Review on Pedagogical Conversational Agents
Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education
Conceptualizing Immersion for Individual Learning in Virtual Reality
Designing a Flipped Classroom Course â a Process Model
The Influence of Risk-Taking on Knowledge Exchange and Combination
Gamified Feedback durch Avatare im Mobile Learning
Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks
Track 5: Data Science & Business Analytics
Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness
Applied image recognition: guidelines for using deep learning models in practice
Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting
Reading Between the Lines of Qualitative Data â How to Detect Hidden Structure Based on Codes
Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation
Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data
Topic Embeddings â A New Approach to Classify Very Short Documents Based on Predefined Topics
Leveraging Unstructured Image Data for Product Quality Improvement
Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest
Knowledge Discovery from CVs: A Topic Modeling Procedure
Online Product Descriptions â Boost for your Sales?
EntscheidungsunterstĂŒtzung durch historienbasierte Dienstreihenfolgeplanung mit Pattern
A Semi-Automated Approach for Generating Online Review Templates
Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization
Bedeutung von Predictive Analytics fĂŒr den theoretischen Erkenntnisgewinn in der IS-Forschung
Track 6: Digitale Transformation und Dienstleistungen
Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems
Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey
Taxonomy of Digital Platforms: A Platform Architecture Perspective
Value of Star Players in the Digital Age
Local Shopping Platforms â Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis
A Socio-Technical Approach to Manage Analytics-as-a-Service â Results of an Action Design Research Project
Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units
Expectations vs. Reality â Benefits of Smart Services in the Field of Tension between Industry and Science
Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment
Characterising Social Reading Platformsâ A Taxonomy-Based Approach to Structure the Field
Less Complex than Expected â What Really Drives IT Consulting Value
Modularity Canvas â A Framework for Visualizing Potentials of Service Modularity
Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things
A Taxonomy of Barriers to Digital Transformation
Ambidexterity in Service Innovation Research: A Systematic Literature Review
Design and success factors of an online solution for cross-pillar pension information
Track 7: IT-Management und -Strategie
A Frugal Support Structure for New Software Implementations in SMEs
How to Structure a Company-wide Adoption of Big Data Analytics
The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age
Bewertung des Kundennutzens von Chatbots fĂŒr den Einsatz im Servicedesk
Understanding the Benefits of Agile Software Development in Regulated Environments
Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies
Agile and Attached: The Impact of Agile Practices on Agile Team Membersâ Affective Organisational Commitment
The Complexity Trap â Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations
Platform Openness: A Systematic Literature Review and Avenues for Future Research
Competence, Fashion and the Case of Blockchain
The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity
Track 8: eHealth & alternde Gesellschaft
Security and Privacy of Personal Health Records in Cloud Computing Environments â An Experimental Exploration of the Impact of Storage Solutions and Data Breaches
Patientenintegration durch Pfadsysteme
Digitalisierung in der StressprĂ€vention â eine qualitative Interviewstudie zu Nutzenpotenzialen
User Dynamics in Mental Health Forums â A Sentiment Analysis Perspective
Intent and the Use of Wearables in the Workplace â A Model Development
Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review
Understanding the Habitual Use of Wearable Activity Trackers
On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Usersâ Goal Orientations in Affecting the Benefits Gained
Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects
Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings
Track 9: Krisen- und KontinuitÀtsmanagement
Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland
Fake News Perception in Germany: A Representative Study of Peopleâs Attitudes and Approaches to Counteract Disinformation
Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment
Track 10: Human-Computer Interaction
Towards a Taxonomy of Platforms for Conversational Agent Design
Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis
Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment
Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren
Designing Dynamic Decision Support for Electronic Requirements Negotiations
Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress
Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents
Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review
Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach
The Role of Early User Participation in Discovering Software â A Case Study from the Context of Smart Glasses
The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games
Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods
Track 11: Information Security and Information Privacy
Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions
To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context
Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR
On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market
What is Your Selfie Worth? A Field Study on Individualsâ Valuation of Personal Data
Justification of Mass Surveillance: A Quantitative Study
An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms
Track 12: Umweltinformatik und nachhaltiges Wirtschaften
KommunikationsfĂ€den im Nadelöhr â Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt
Potentiale und Herausforderungen der Materialflusskostenrechnung
Computing Incentives for User-Based Relocation in Carsharing
Sustainabilityâs Coming Home: Preliminary Design Principles for the Sustainable Smart District
Substitution of hazardous chemical substances using Deep Learning and t-SNE
A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment
A Survey of Smart Energy Services for Private Households
Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation â A Literature Review
Ein EntscheidungsunterstĂŒtzungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse
Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy
Digitale RĂŒckverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie
Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones
Towards Predictive Energy Management in Information Systems: A Research Proposal
A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology
Track 13: Digital Work - Social, mobile, smart
On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work
The Potential of Augmented Reality for Improving Occupational First Aid
Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants
Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI
A Case Study on Cross-Hierarchical Communication in Digital Work Environments
âShow Me Your People Skillsâ - Employing CEO Branding for Corporate Reputation Management in Social Media
A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change
The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects
The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance
Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp
The Effect of Marker-less Augmented Reality on Task and Learning Performance
Antecedents for Cyberloafing â A Literature Review
Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project
Track 14: GeschÀftsmodelle und digitales Unternehmertum
Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes
Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services
Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective
Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction
Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes
Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators
When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies
Special Track 1: Student Track
Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail
From Facets to a Universal Definition â An Analysis of IoT Usage in Retail
Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study
Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking
TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter
Application of Process Mining Techniques to Support Maintenance-Related Objectives
How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce
Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance?
Improving Business Model Configuration through a Question-based Approach
The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning
Evaluation von ITSM-Tools fĂŒr Integration und Management von Cloud-Diensten am Beispiel von ServiceNow
How Software Promotes the Integration of Sustainability in Business Process Management
Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry
Special Track 3: Demos & Prototyping
Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype
Application-oriented robotics in nursing homes
Augmented Reality for Set-up Processe
Mixed Reality for supporting Remote-Meetings
Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung
Automatically Extracting and Analyzing Customer Needs from Twitter: A âNeedminingâ Prototype
GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities
TUCANA: A platform for using local processing power of edge devices for building data-driven services
Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur
Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation fĂŒr Ă€ltere Nutzerinnen und Nutzer
A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach
Exergames & Dementia: An interactive System for People with Dementia and their Care-Network
Workshops
Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik â EMoWIâ19)
Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates
Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management
Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research
Die Mitarbeiter von morgen - Kompetenzen kĂŒnftiger Mitarbeiter im Bereich Business Analytics
Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati
Proceedings of the 11th international Conference on Cognitive Modeling : ICCM 2012
The International Conference on Cognitive Modeling (ICCM) is the premier conference for research on computational models and computation-based theories of human behavior. ICCM is a forum for presenting, discussing, and evaluating the complete spectrum of cognitive modeling approaches, including connectionism, symbolic modeling, dynamical systems, Bayesian modeling, and cognitive architectures. ICCM includes basic and applied research, across a wide variety of domains, ranging from low-level perception and attention to higher-level problem-solving and learning. Online-Version published by UniversitÀtsverlag der TU Berlin (www.univerlag.tu-berlin.de
Brain Computations and Connectivity [2nd edition]
This is an open access title available under the terms of a CC BY-NC-ND 4.0 International licence. It is free to read on the Oxford Academic platform and offered as a free PDF download from OUP and selected open access locations.
Brain Computations and Connectivity is about how the brain works. In order to understand this, it is essential to know what is computed by different brain systems; and how the computations are performed.
The aim of this book is to elucidate what is computed in different brain systems; and to describe current biologically plausible computational approaches and models of how each of these brain systems computes.
Understanding the brain in this way has enormous potential for understanding ourselves better in health and in disease. Potential applications of this understanding are to the treatment of the brain in disease; and to artificial intelligence which will benefit from knowledge of how the brain performs many of its extraordinarily impressive functions.
This book is pioneering in taking this approach to brain function: to consider what is computed by many of our brain systems; and how it is computed, and updates by much new evidence including the connectivity of the human brain the earlier book: Rolls (2021) Brain Computations: What and How, Oxford University Press.
Brain Computations and Connectivity will be of interest to all scientists interested in brain function and how the brain works, whether they are from neuroscience, or from medical sciences including neurology and psychiatry, or from the area of computational science including machine learning and artificial intelligence, or from areas such as theoretical physics