Check computer science papers: citations, claims and retractions

A Review of Wearable Solutions for Physiological and Emotional Monitoring for Use by People with Autism Spectrum Disorder and Their Caregivers

Taj-Eldin, M., Ryan, C., O’Flynn, B., & Galvin, P. (2018) · Sensors

Emotion and Mood RecognitionAutism Spectrum Disorder Research

Cited by 142

The Role of Hubness in Clustering High-Dimensional Data

Tomasev, N., Radovanovic, M., Mladenic, D., & Ivanovic, M. (2014) · IEEE Transactions on Knowledge and Data Engineering

Advanced Clustering Algorithms ResearchMachine Learning and Data Classification

Cited by 142

Ultrasound image analysis using deep neural networks for discriminating between benign and malignant ovarian tumors: Comparison with expert subjective assessment

Christiansen, F., Epstein, E. L., Smedberg, E., Åkerlund, M., Smith, K., & Epstein, E. (2021) · Ultrasound in Obstetrics & Gynecology

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 142

Efficient Synthesis of Universal Repeat-Until-Success Quantum Circuits

Bocharov, A., Roetteler, M., & Svore, K. M. (2015) · Physical Review Letters

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 142

GPU-Qin: A methodology for evaluating the error resilience of GPGPU applications

Fang, B., Pattabiraman, K., Ripeanu, M., & Gurumurthi, S. (2014) · 2014 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)

Distributed systems and fault toleranceParallel Computing and Optimization Techniques

Cited by 142

esDNN: Deep Neural Network Based Multivariate Workload Prediction in Cloud Computing Environments

Xu, M., Song, C., Wu, H., Gill, S. S., Ye, K., & Xu, C. (2022) · ACM Transactions on Internet Technology

Cloud Computing and Resource ManagementEnergy Efficiency in Computing

Cited by 142

Generative AI as a transformative force for innovation: a review of opportunities, applications and challenges

Sedkaoui, S., & Benaichouba, R. (2026) · European Journal of Innovation Management

Artificial Intelligence ApplicationsImpact of AI and Big Data on Business and Society

Cited by 142

Fast generation of digitally reconstructed radiographs using attenuation fields with application to 2D-3D image registration

Russakoff, D. B., Rohlfing, T., Mori, K., Rueckert, D., Ho, A., Adler, J. R., & Maurer, C. R. (2005) · IEEE Transactions on Medical Imaging

Medical Image Segmentation TechniquesAdvanced Radiotherapy Techniques

Cited by 142

Interpretation of deep learning in genomics and epigenomics

Talukder, A., Barham, C., Li, X., & Hu, H. (2021) · Briefings in Bioinformatics

Explainable Artificial Intelligence (XAI)Machine Learning in Bioinformatics

Cited by 142

FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning

Kuang, W., Qian, B., Li, Z., Chen, D., Gao, D., Pan, X., Xie, Y., Li, Y., Ding, B., & Zhou, J. (2024) · Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Privacy-Preserving Technologies in DataTopic Modeling

Cited by 142

TweetNLP: Cutting-Edge Natural Language Processing for Social Media

Camacho-collados, J., Rezaee, K., Riahi, T., Ushio, A., Loureiro, D., Antypas, D., Boisson, J., Espinosa Anke, L., Liu, F., & Martínez Cámara, E. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 142

Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images

Ma, J., Wu, F., Jiang, T., Zhu, J., & Kong, D. (2017) · Medical Physics

AI in cancer detectionMedical Image Segmentation Techniques

Cited by 142

Deep Reinforcement Learning at the Edge of the Statistical Precipice

Agarwal, R., Schwarzer, M., Castro, P. S., Courville, A., & Bellemare, M. G. (2021) · arXiv

Reinforcement Learning in RoboticsArtificial Intelligence in Games

Cited by 142

Retentive Network: A Successor to Transformer for Large Language Models

Sun, Y., Dong, L., Huang, S., Ma, S., Xia, Y., Xue, J., Wang, J., & Wei, F. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 142

Toward Artificial Argumentation

Atkinson, K., Baroni, P., Giacomin, M., Hunter, A., Prakken, H., Reed, C., Simari, G., Thimm, M., & Villata, S. (2017) · AI Magazine

Multi-Agent Systems and NegotiationLogic, Reasoning, and Knowledge

Cited by 142

Translating Images into Maps

Saha, A., Maldonado, O. M., Russell, C., & Bowden, R. (2021) · arXiv

Robotics and Sensor-Based LocalizationAdvanced Neural Network Applications

Cited by 142

“Transforming” Delete, Retrieve, Generate Approach for Controlled Text Style Transfer

Sudhakar, A., Upadhyay, B., & Maheswaran, A. (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 142

FERAtt: Facial Expression Recognition With Attention Net

Fernandez, P. D. M., Pena, F. A. G., Ren, T. I., & Cunha, A. (2019) · 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Emotion and Mood RecognitionFace recognition and analysis

Cited by 142

Simultaneous measurement of the phase and group indices and the thickness of transparent plates by low-coherence interferometry

Haruna, M., Ohmi, M., Mitsuyama, T., Tajiri, H., Maruyama, H., & Hashimoto, M. (1998) · Optics Letters

Optical measurement and interference techniquesOptical Coherence Tomography Applications

Cited by 142

Blocking and array contraction across arbitrarily nested loops using affine partitioning

Lim, A. W., Liao, S.-W., & Lam, M. S. (2001) · Proceedings of the eighth ACM SIGPLAN symposium on Principles and practices of parallel programming

Parallel Computing and Optimization TechniquesComputer Graphics and Visualization Techniques

Cited by 142

Approximate Quantum Error Correction

Schumacher, B., & Westmoreland, M. D. (2002) · Quantum Information Processing

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 142

A survey of AIOps methods for failure management

Notaro, P., Cardoso, J., & Gerndt, M. (2021) · ACM Transactions on Intelligent Systems and Technology

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 142

Segmentation-Aware Convolutional Networks Using Local Attention Masks

Harley, A. W., Derpanis, K. G., & Kokkinos, I. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV)

Advanced Neural Network ApplicationsVisual Attention and Saliency Detection

Cited by 142

Who Will Stay in the FLOSS Community? Modeling Participant’s Initial Behavior

Zhou, M., & Mockus, A. (2015) · IEEE Transactions on Software Engineering

Open Source Software InnovationsSoftware Engineering Techniques and Practices

Cited by 141