Check computer science papers: citations, claims and retractions

An Analysis of Deep Neural Network Models for Practical Applications

Canziani, A., Paszke, A., & Culurciello, E. (2016) · arXiv

Advanced Neural Network ApplicationsParallel Computing and Optimization Techniques

Cited by 969

SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud

Wu, B., Wan, A., Yue, X., & Keutzer, K. (2018) · 2018 IEEE International Conference on Robotics and Automation (ICRA)

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 967

Local Graph Partitioning using PageRank Vectors

Andersen, R., Chung, F., & Lang, K. (2006) · 2006 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS'06)

Complexity and Algorithms in GraphsComplex Network Analysis Techniques

Cited by 967

Overview and Evaluation of Bluetooth Low Energy: An Emerging Low-Power Wireless Technology

Gomez, C., Oller, J., & Paradells, J. (2012) · Sensors

Bluetooth and Wireless Communication TechnologiesWireless Body Area Networks

Cited by 967

Putting yourself in the skin of a black avatar reduces implicit racial bias

Peck, T. C., Seinfeld, S., Aglioti, S. M., & Slater, M. (2013) · Consciousness and Cognition

Virtual Reality Applications and ImpactsSocial and Intergroup Psychology

Cited by 967

A visual-language foundation model for computational pathology

Lu, M. Y., Chen, B., Williamson, D. F. K., Chen, R. J., Liang, I., Ding, T., Jaume, G., Odintsov, I., Le, L. P., Gerber, G., et al. (2024) · Nature Medicine

Multimodal Machine Learning ApplicationsAI in cancer detection

Cited by 966

Flamingo: a visual language model for few-shot learning

Alayrac, J.-B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al. (2022) · Advances in Neural Information Processing Systems 35

Domain Adaptation and Few-Shot LearningMultimodal Machine Learning Applications

Cited by 966

Attention is not not Explanation

Wiegreffe, S., & Pinter, Y. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Natural Language Processing TechniquesTopic Modeling

Cited by 966

Value-sensitive design

Friedman, B. (1996) · Interactions

Innovative Human-Technology InteractionUsability and User Interface Design

Cited by 966

Large scale deep learning for computer aided detection of mammographic lesions

Kooi, T., Litjens, G., van Ginneken, B., Gubern-Mérida, A., Sánchez, C. I., Mann, R., den Heeten, A., & Karssemeijer, N. (2017) · Medical Image Analysis

AI in cancer detectionDigital Radiography and Breast Imaging

Cited by 965

Alexa, Siri, Cortana, and more: An introduction to voice assistants.

Hoy, M. B. (2018) · Medical Reference Services Quarterly

Speech and dialogue systemsAI in Service Interactions

Cited by 965

Machine learning in wireless sensor networks: Algorithms, strategies, and applications

Alsheikh, M. A., Lin, S., Niyato, D., & Tan, H.-P. (2014) · IEEE Communications Surveys & Tutorials

Energy Efficient Wireless Sensor NetworksWireless Sensor Networks for Data Analysis

Cited by 965

Ensemble quantum computing by NMR spectroscopy

Cory, D. G., Fahmy, A. F., & Havel, T. F. (1997) · Proceedings of the National Academy of Sciences

Quantum Computing Algorithms and ArchitectureDNA and Biological Computing

Cited by 964

Pros and cons of GAN evaluation measures

Borji, A. (2019) · Computer Vision and Image Understanding

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 963

A BEHAVIOURAL APPROACH TO INFORMATION RETRIEVAL SYSTEM DESIGN

ELLIS, D. (1989) · Journal of Documentation

Information Retrieval and Search BehaviorLibrary Science and Information Literacy

Cited by 962

Why CSCW applications fail: problems in the design and evaluationof organizational interfaces

Grudin, J. (1988) · Proceedings of the 1988 ACM conference on Computer-supported cooperative work - CSCW '88

Usability and User Interface DesignInformation Systems Theories and Implementation

Cited by 961

Recommended Steps for Thematic Synthesis in Software Engineering

Cruzes, D. S., & Dyba, T. (2011) · 2011 International Symposium on Empirical Software Engineering and Measurement

Software Engineering Techniques and PracticesMeta-analysis and systematic reviews

Cited by 960

The experimental induction of out-of-body experiences

Ehrsson, H. H. (2007) · Science

Virtual Reality Applications and ImpactsMultisensory perception and integration

Cited by 959

Multitask learning and benchmarking with clinical time series data

Harutyunyan, H., Khachatrian, H., Kale, D. C., Ver Steeg, G., & Galstyan, A. (2019) · Scientific Data

Machine Learning in HealthcareArtificial Intelligence in Healthcare

Cited by 958

Interpretable machine learning: Fundamental principles and 10 grand challenges

Rudin, C., Chen, C., Chen, Z., Huang, H., Semenova, L., & Zhong, C. (2022) · Statistics Surveys

Explainable Artificial Intelligence (XAI)Machine Learning and Data Classification

Cited by 958

Soli: ubiquitous gesture sensing with millimeter wave radar

Lien, J., Gillian, N., Karagozler, M. E., Amihood, P., Schwesig, C., Olson, E., Raja, H., & Poupyrev, I. (2016) · ACM Transactions on Graphics

Hand Gesture Recognition SystemsInteractive and Immersive Displays

Cited by 957

Multi-agent deep reinforcement learning: a survey

Gronauer, S., & Diepold, K. (2022) · Artificial Intelligence Review

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 957

Dual-stream Multiple Instance Learning Network for Whole Slide Image Classification with Self-supervised Contrastive Learning

Li, B., Li, Y., & Eliceiri, K. W. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 957

What is embodiment? A psychometric approach

Longo, M. R., Schüür, F., Kammers, M. P. M., Tsakiris, M., & Haggard, P. (2008) · Cognition

Virtual Reality Applications and ImpactsFree Will and Agency

Cited by 956