Check computer science papers: citations, claims and retractions

Contrastive Self-supervised Learning for Sensor-based Human Activity Recognition

Khaertdinov, B., Ghaleb, E., & Asteriadis, S. (2021) · 2021 IEEE International Joint Conference on Biometrics (IJCB)

Context-Aware Activity Recognition SystemsDomain Adaptation and Few-Shot Learning

Cited by 95

Redefining boundaries in innovation and knowledge domains: Investigating the impact of generative artificial intelligence on copyright and intellectual property rights

Al-Busaidi, A. S., Raman, R., Hughes, L., Albashrawi, M. A., Malik, T., Dwivedi, Y. K., Al- Alawi, T., AlRizeiqi, M., Davies, G., Fenwick, M., et al. (2024) · Journal of Innovation & Knowledge

Law, AI, and Intellectual PropertyIntellectual Property Law

Cited by 95

SpaceNet MVOI: A Multi-View Overhead Imagery Dataset

Weir, N., Lindenbaum, D., Bastidas, A., Etten, A., Kumar, V., Mcpherson, S., Shermeyer, J., & Tang, H. (2019) · 2019 IEEE/CVF International Conference on Computer Vision (ICCV)

Automated Road and Building ExtractionAdvanced Neural Network Applications

Cited by 95

BlenderBot 3: a deployed conversational agent that continually learns to responsibly engage

Shuster, K., Xu, J., Komeili, M., Ju, D., Smith, E. M., Roller, S., Ung, M., Chen, M., Arora, K., Lane, J., et al. (2022) · arXiv

Speech and dialogue systemsAI in Service Interactions

Cited by 95

Lagrangian duality in 3D SLAM: Verification techniques and optimal solutions

Carlone, L., Rosen, D. M., Calafiore, G., Leonard, J. J., & Dellaert, F. (2015) · 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Robotics and Sensor-Based LocalizationTarget Tracking and Data Fusion in Sensor Networks

Cited by 95

Twitch crowdsourcing: crowd contributions in short bursts of time

Vaish, R., Wyngarden, K., Chen, J., Cheung, B., & Bernstein, M. S. (2014) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Mobile Crowdsensing and CrowdsourcingUsability and User Interface Design

Cited by 95

Generate rather than Retrieve: Large Language Models are Strong Context Generators

Yu, W., Iter, D., Wang, S., Xu, Y., Ju, M., Sanyal, S., Zhu, C., Zeng, M., & Jiang, M. (2022) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 95

Mass personalization: Predictive marketing algorithms and the reshaping of consumer knowledge

Kotras, B. (2020) · Big Data & Society

Ethics and Social Impacts of AIBig Data Technologies and Applications

Cited by 95

Backdoor Defense with Machine Unlearning

Liu, Y., Fan, M., Chen, C., Liu, X., Ma, Z., Wang, L., & Ma, J. (2022) · IEEE INFOCOM 2022 - IEEE Conference on Computer Communications

Adversarial Robustness in Machine LearningSecurity and Verification in Computing

Cited by 95

Artificial intelligence in dermatopathology: diagnosis, education, and research

Wells, A., Patel, S., Lee, J. B., & Motaparthi, K. (2021) · Journal of Cutaneous Pathology

AI in cancer detectionCutaneous Melanoma Detection and Management

Cited by 95

Augmented Intelligence of Things for Emergency Vehicle Secure Trajectory Prediction and Task Offloading

Wu, X., Dong, J., Bao, W., Zou, B., Wang, L., & Wang, H. (2024) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingVehicular Ad Hoc Networks (VANETs)

Cited by 95

Logical Neural Networks

Riegel, R., Gray, A., Luus, F., Khan, N., Makondo, N., Akhalwaya, I. Y., Qian, H., Fagin, R., Barahona, F., Sharma, U., et al. (2020) · arXiv

Logic, Reasoning, and KnowledgeNeural Networks and Applications

Cited by 95

Flag Fault-Tolerant Error Correction for any Stabilizer Code

Chao, R., & Reichardt, B. W. (2020) · PRX Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 95

How to regulate algorithmic decision-making: A framework of regulatory requirements for different applications

Krafft, T. D., Zweig, K. A., & König, P. D. (2022) · Regulation & Governance

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 95

Multi-Modal Attention for Speech Emotion Recognition

Pan, Z., Luo, Z., Yang, J., & Li, H. (2020) · Interspeech 2020

Emotion and Mood RecognitionSpeech Recognition and Synthesis

Cited by 95

One-Network Adversarial Fairness

Adel, T., Valera, I., Ghahramani, Z., & Weller, A. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Ethics and Social Impacts of AIExplainable Artificial Intelligence (XAI)

Cited by 95

Exploring ethics and human rights in artificial intelligence – A Delphi study

Stahl, B. C., Brooks, L., Hatzakis, T., Santiago, N., & Wright, D. (2023) · Technological Forecasting and Social Change

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 95

PMC: A Privacy-preserving Deep Learning Model Customization Framework for Edge Computing

Liu, B., Li, Y., Liu, Y., Guo, Y., & Chen, X. (2020) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Privacy-Preserving Technologies in DataDomain Adaptation and Few-Shot Learning

Cited by 95

Seahawk: Stack Overflow in the IDE

Ponzanelli, L., Bacchelli, A., & Lanza, M. (2013) · 2013 35th International Conference on Software Engineering (ICSE)

Software Engineering ResearchExpert finding and Q&A systems

Cited by 95

Do We Train on Test Data? Purging CIFAR of Near-Duplicates

Barz, B., & Denzler, J. (2020) · Journal of Imaging

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 95

Cross-scale multi-instance learning for pathological image diagnosis

Deng, R., Cui, C., Remedios, L. W., Bao, S., Womick, R. M., Chiron, S., Li, J., Roland, J. T., Lau, K. S., Liu, Q., et al. (2024) · Medical Image Analysis

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 95

The Surprising Effectiveness of Representation Learning for Visual Imitation

Pari, J., Shafiullah, N. M. (., Arunachalam, S. P., & Pinto, L. (2022) · Robotics: Science and Systems XVIII

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 95

Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning

Namburete, A. I. L., Xie, W., Yaqub, M., Zisserman, A., & Noble, J. A. (2018) · Medical Image Analysis

Medical Image Segmentation TechniquesFetal and Pediatric Neurological Disorders

Cited by 95

Facilitators and barriers to engagement with contact tracing during infectious disease outbreaks: a rapid review of the evidence

Megnin-Viggars, O., Carter, P., Melendez-Torres, G. J., Weston, D., & Rubin, G. J. (2020) · PLOS ONE

COVID-19 Digital Contact TracingMobile Health and mHealth Applications

Cited by 95