Check computer science papers: citations, claims and retractions

A language framework for modeling social media account behavior

Nwala, A. C., Flammini, A., & Menczer, F. (2023) · EPJ Data Science

Spam and Phishing DetectionMisinformation and Its Impacts

Cited by 31

Neural Signatures of User-Centered Security: An fMRI Study of Phishing, and Malware Warnings

Neupane, A., Saxena, N., Kuruvilla, K., Georgescu, M., & Kana, R. (2014) · Proceedings 2014 Network and Distributed System Security Symposium

Spam and Phishing DetectionUser Authentication and Security Systems

Cited by 31

Implementation of multiple specialization in logic programs

Puebla, G., & Hermenegildo, M. (1995) · Proceedings of the 1995 ACM SIGPLAN symposium on Partial evaluation and semantics-based program manipulation - PEPM '95

Logic, programming, and type systemsParallel Computing and Optimization Techniques

Cited by 31

Tablets for teaching and learning: A systematic review and meta-analysis

Tamim, R., Borokhovski, E., Pickup, D., Bernard, R. M., & Saadi, L. E. (2015) · Commonwealth of Learning

Mobile Learning in EducationEducation and Technology Integration

Cited by 31

Cybersecurity Model Based on Hardening for Secure Internet of Things Implementation

Echeverría, A., Cevallos, C., Ortiz-Garces, I., & Andrade, R. O. (2021) · Applied Sciences

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 31

Topological Graph Neural Networks

Horn, M., De Brouwer, E., Moor, M., Moreau, Y., Rieck, B., & Borgwardt, K. (2021) · arXiv

Advanced Graph Neural NetworksTopological and Geometric Data Analysis

Cited by 31

Cyber security attacks on robotic platforms

Bhardwaj, A., Avasthi, V., & Goundar, S. (2019) · Network Security

Information and Cyber SecurityAdversarial Robustness in Machine Learning

Cited by 31

MixQG: Neural Question Generation with Mixed Answer Types

Murakhovs’ka, L., Wu, C.-S., Laban, P., Niu, T., Liu, W., & Xiong, C. (2022) · Findings of the Association for Computational Linguistics: NAACL 2022

Topic ModelingNatural Language Processing Techniques

Cited by 31

Practical experience of virtual team software development

Casey, V., & Richardson, I. (2004) · University of Limerick

Software Engineering Techniques and PracticesTeam Dynamics and Performance

Cited by 31

Explainable Time Series Tweaking via Irreversible and Reversible Temporal Transformations

Karlsson, I., Rebane, J., Papapetrou, P., & Gionis, A. (2018) · 2018 IEEE International Conference on Data Mining (ICDM)

Time Series Analysis and ForecastingExplainable Artificial Intelligence (XAI)

Cited by 31

A federated learning architecture for secure and private neuroimaging analysis

Stripelis, D., Gupta, U., Saleem, H., Dhinagar, N., Ghai, T., Anastasiou, C., Sánchez, R., Steeg, G. V., Ravi, S., Naveed, M., et al. (2024) · Patterns

Privacy-Preserving Technologies in DataCryptography and Data Security

Cited by 31

Computational Difficulty of Computing the Density of States

Brown, B., Flammia, S. T., & Schuch, N. (2011) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 31

A Study of Defensive Methods to Protect Visual Recommendation Against Adversarial Manipulation of Images

Anelli, V. W., Deldjoo, Y., Di Noia, T., Malitesta, D., & Merra, F. A. (2021) · Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval

Adversarial Robustness in Machine LearningRecommender Systems and Techniques

Cited by 31

Detection of anomalous vehicle trajectories using federated learning

Koetsier, C., Fiosina, J., Gremmel, J. N., Müller, J. P., Woisetschläger, D. M., & Sester, M. (2022) · ISPRS Open Journal of Photogrammetry and Remote Sensing

Anomaly Detection Techniques and ApplicationsPrivacy-Preserving Technologies in Data

Cited by 31

Data excellence for AI: why should you care?

Aroyo, L., Lease, M., Paritosh, P., & Schaekermann, M. (2022) · Interactions

Innovative Human-Technology InteractionEthics and Social Impacts of AI

Cited by 31

AdaPlanner: Adaptive Planning from Feedback with Language Models

Sun, H., Zhuang, Y., Kong, L., Dai, B., & Zhang, C. (2023) · Advances in Neural Information Processing Systems 36

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 31

DF-VO: What Should Be Learnt for Visual Odometry?

Zhan, H., Weerasekera, C. S., Bian, J.-W., Garg, R., & Reid, I. (2021) · arXiv

Robotics and Sensor-Based LocalizationAdvanced Vision and Imaging

Cited by 31

Augmented reality tour system for immersive experience of cultural heritage

Kim, K., Seo, B.-K., Han, J.-H., & Park, J.-I. (2009) · Proceedings of the 8th International Conference on Virtual Reality Continuum and its Applications in Industry

Augmented Reality ApplicationsMuseums and Cultural Heritage

Cited by 31

Performance evaluation of public-key cryptosystem operations in WTLS protocol

Levi, A., & Savas, E. (2004) · Proceedings of the Eighth IEEE Symposium on Computers and Communications. ISCC 2003

Cryptography and Residue ArithmeticAdvanced Authentication Protocols Security

Cited by 31

Self-supervised Learning for Single View Depth and Surface Normal Estimation

Zhan, H., Weerasekera, C. S., Garg, R., & Reid, I. (2019) · 2019 International Conference on Robotics and Automation (ICRA)

Advanced Vision and Imaging3D Shape Modeling and Analysis

Cited by 31

Schedule path optimization for adiabatic quantum computing and optimization

Zeng, L., Zhang, J., & Sarovar, M. (2016) · Journal of Physics A: Mathematical and Theoretical

Quantum Computing Algorithms and ArchitectureQuantum many-body systems

Cited by 31

AyaTEC: Building a Reusable Verse-Based Test Collection for Arabic Question Answering on the Holy Qur’an

Malhas, R., & Elsayed, T. (2020) · ACM Transactions on Asian and Low-Resource Language Information Processing

Information Retrieval and Search BehaviorNatural Language Processing Techniques

Cited by 31

Moving faster than the COVID-19 pandemic: The rapid, digital transformation of a public health system

Sullivan, C., Wong, I., Adams, E., Fahim, M., Fraser, J., Ranatunga, G., Busato, M., & McNeil, K. (2021) · Applied Clinical Informatics

COVID-19 Digital Contact TracingHealthcare during COVID-19 Pandemic

Cited by 31

Secure and Lightweight Compressive Sensing Using Stream Cipher

Pudi, V., Chattopadhyay, A., & Lam, K.-Y. (2018) · IEEE Transactions on Circuits and Systems II: Express Briefs

Sparse and Compressive Sensing TechniquesChaos-based Image/Signal Encryption

Cited by 31