Check computer science papers: citations, claims and retractions

The Creation and Detection of Deepfakes: A Survey

Mirsky, Y., & Lee, W. (2020) · arXiv

Digital Media Forensic DetectionGenerative Adversarial Networks and Image Synthesis

Cited by 863

Japanese and Korean voice search

Schuster, M., & Nakajima, K. (2012) · 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech Recognition and SynthesisSpeech and dialogue systems

Cited by 862

Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

Lin, G., Shen, C., van den Hengel, A., & Reid, I. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Advanced Neural Network ApplicationsMedical Image Segmentation Techniques

Cited by 862

The use of virtual reality technology in the treatment of anxiety and other psychiatric disorders

Maples-Keller, J. L., Bunnell, B. E., Kim, S.-J., & Rothbaum, B. O. (2017) · Harvard Review of Psychiatry

Virtual Reality Applications and ImpactsDigital Mental Health Interventions

Cited by 862

Contrastive Representation Learning: A Framework and Review

Le-Khac, P. H., Healy, G., & Smeaton, A. F. (2020) · IEEE Access

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 862

On Using Very Large Target Vocabulary for Neural Machine Translation

Jean, S., Cho, K., Memisevic, R., & Bengio, Y. (2015) · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

Natural Language Processing TechniquesTopic Modeling

Cited by 862

Blockchain-based traceability in Agri-Food supply chain management: A practical implementation

Caro, M. P., Ali, M. S., Vecchio, M., & Giaffreda, R. (2018) · 2018 IoT Vertical and Topical Summit on Agriculture - Tuscany (IOT Tuscany)

Blockchain Technology Applications and SecurityFood Supply Chain Traceability

Cited by 861

Transfer Learning in Deep Reinforcement Learning: A Survey

Zhu, Z., Lin, K., Jain, A. K., & Zhou, J. (2023) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 861

Automatic Segmentation of MR Brain Images With a Convolutional Neural Network

Moeskops, P., Viergever, M. A., Mendrik, A. M., de Vries, L. S., Benders, M. J. N. L., & Isgum, I. (2016) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 861

"Do Anything Now": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models

Shen, X., Chen, Z., Backes, M., Shen, Y., & Zhang, Y. (2023) · arXiv

Adversarial Robustness in Machine LearningHate Speech and Cyberbullying Detection

Cited by 861

Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning

Jagielski, M., Oprea, A., Biggio, B., Liu, C., Nita-Rotaru, C., & Li, B. (2018) · 2018 IEEE Symposium on Security and Privacy (SP)

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 861

Implications for design

Dourish, P. (2006) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

Usability and User Interface DesignInnovative Human-Technology Interaction

Cited by 860

Sparse geometric image representations with bandelets

Le Pennec, E., & Mallat, S. (2005) · IEEE Transactions on Image Processing

Advanced Data Compression TechniquesImage and Signal Denoising Methods

Cited by 860

Deep Learning Based Communication Over the Air

Dorner, S., Cammerer, S., Hoydis, J., & Brink, S. T. (2018) · IEEE Journal of Selected Topics in Signal Processing

Wireless Signal Modulation ClassificationAdvanced Wireless Communication Techniques

Cited by 859

When does label smoothing help?

Müller, R., Kornblith, S., & Hinton, G. (2019) · arXiv

Domain Adaptation and Few-Shot LearningAdvanced Neural Network Applications

Cited by 859

CGNet: A Light-Weight Context Guided Network for Semantic Segmentation

Wu, T., Tang, S., Zhang, R., Cao, J., & Zhang, Y. (2021) · IEEE Transactions on Image Processing

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 859

A curated mammography data set for use in computer-aided detection and diagnosis research

Lee, R. S., Gimenez, F., Hoogi, A., Miyake, K. K., Gorovoy, M., & Rubin, D. L. (2017) · Scientific Data

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 859

Virtual Reality for Health Professions Education: Systematic Review and Meta-Analysis by the Digital Health Education Collaboration

Kyaw, B. M., Saxena, N., Posadzki, P., Vseteckova, J., Nikolaou, C. K., George, P. P., Divakar, U., Masiello, I., Kononowicz, A. A., Zary, N., et al. (2019) · Journal of Medical Internet Research

Virtual Reality Applications and ImpactsSimulation-Based Education in Healthcare

Cited by 859

Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy

Fiske, A., Henningsen, P., & Buyx, A. (2019) · Journal of Medical Internet Research

Ethics and Social Impacts of AIArtificial Intelligence in Healthcare and Education

Cited by 857

The state of the art in online handwriting recognition

Tappert, C. C., Suen, C. Y., & Wakahara, T. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence

Handwritten Text Recognition TechniquesVehicle License Plate Recognition

Cited by 857

A Survey of Model Compression and Acceleration for Deep Neural Networks

Cheng, Y., Wang, D., Zhou, P., & Zhang, T. (2017) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 857

Evaluation of prostate segmentation algorithms for mri: The promise12 challenge

Litjens, G., Toth, R., van de Ven, W., Hoeks, C., Kerkstra, S., van Ginneken, B., Vincent, G., Guillard, G., Birbeck, N., Zhang, J., et al. (2014) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 857

Edge Computing in Industrial Internet of Things: Architecture, Advances and Challenges

Qiu, T., Chi, J., Zhou, X., Ning, Z., Atiquzzaman, M., & Wu, D. O. (2020) · IEEE Communications Surveys & Tutorials

IoT and Edge/Fog ComputingDigital Transformation in Industry

Cited by 857

A critique of ANSI SQL isolation levels

Berenson, H., Bernstein, P., Gray, J., Melton, J., O'Neil, E., & O'Neil, P. (1995) · Proceedings of the 1995 ACM SIGMOD international conference on Management of data - SIGMOD '95

Distributed systems and fault toleranceAdvanced Database Systems and Queries

Cited by 856