Check computer science papers: citations, claims and retractions

Multisensory stimulation can induce an illusion of larger belly size in immersive virtual reality.

Normand, J.-M., Giannopoulos, E., Spanlang, B., & Slater, M. (2011) · PLoS ONE

Virtual Reality Applications and ImpactsMultisensory perception and integration

Cited by 282

Augmented reality in STEM education: a systematic review

Sırakaya, M., & Alsancak Sırakaya, D. (2022) · Interactive Learning Environments

Augmented Reality ApplicationsSTEM Education

Cited by 282

EDN: Salient Object Detection via Extremely-Downsampled Network

Wu, Y.-H., Liu, Y., Zhang, L., Cheng, M.-M., & Ren, B. (2022) · IEEE Transactions on Image Processing

Visual Attention and Saliency DetectionAdvanced Neural Network Applications

Cited by 282

Inferiority or Even Superiority of Virtual Reality Exposure Therapy in Phobias?—A Systematic Review and Quantitative Meta-Analysis on Randomized Controlled Trials Specifically Comparing the Efficacy of Virtual Reality Exposure to Gold Standard in vivo Exposure in Agoraphobia, Specific Phobia, and Social Phobia

Wechsler, T. F., Kümpers, F., & Mühlberger, A. (2019) · Frontiers in Psychology

Virtual Reality Applications and ImpactsAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes

Cited by 282

Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures

El Kaliouby, R., & Robinson, P. (2005) · 2004 Conference on Computer Vision and Pattern Recognition Workshop

Emotion and Mood RecognitionGaze Tracking and Assistive Technology

Cited by 282

Explainable artificial intelligence for breast cancer: A visual case-based reasoning approach

Lamy, J.-B., Sekar, B., Guezennec, G., Bouaud, J., & Séroussi, B. (2019) · Artificial Intelligence in Medicine

Explainable Artificial Intelligence (XAI)AI-based Problem Solving and Planning

Cited by 282

Building a Fault-Tolerant Quantum Computer Using Concatenated Cat Codes

Chamberland, C., Noh, K., Arrangoiz-Arriola, P., Campbell, E. T., Hann, C. T., Iverson, J., Putterman, H., Bohdanowicz, T. C., Flammia, S. T., Keller, A., et al. (2022) · PRX Quantum

Quantum Computing Algorithms and ArchitectureQuantum Information and Cryptography

Cited by 281

Blockchain-based Personal Health Data Sharing System Using Cloud Storage

Zheng, X., Mukkamala, R. R., Vatrapu, R., & Ordieres-Mere, J. (2018) · 2018 IEEE 20th International Conference on e-Health Networking, Applications and Services (Healthcom)

Blockchain Technology Applications and SecurityCloud Data Security Solutions

Cited by 281

AI in education: learner choice and fundamental rights

Berendt, B., Littlejohn, A., & Blakemore, M. (2020) · Learning, Media and Technology

Ethics and Social Impacts of AIArtificial Intelligence in Education

Cited by 281

GLM-130B: An Open Bilingual Pre-trained Model

Zeng, A., Liu, X., Du, Z., Wang, Z., Lai, H., Ding, M., Yang, Z., Xu, Y., Zheng, W., Xia, X., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 281

Blockchain and Artificial Intelligence Technology in E-Health

Tagde, P., Tagde, S., Bhattacharya, T., Tagde, P., Chopra, H., Akter, R., Kaushik, D., & Rahman, M. H. (2021) · Environmental Science and Pollution Research

Blockchain Technology Applications and SecurityArtificial Intelligence in Healthcare and Education

Cited by 281

A blockchain-based privacy-preserving payment mechanism for vehicle-to-grid networks

Gao, F., Zhu, L., Shen, M., Sharif, K., Wan, Z., & Ren, K. (2018) · IEEE Network

Blockchain Technology Applications and SecurityVehicular Ad Hoc Networks (VANETs)

Cited by 281

Multimodal Deep Learning for Activity and Context Recognition

Radu, V., Tong, C., Bhattacharya, S., Lane, N. D., Mascolo, C., Marina, M. K., & Kawsar, F. (2018) · Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies

Context-Aware Activity Recognition SystemsHuman Mobility and Location-Based Analysis

Cited by 281

A discriminative deep model for pedestrian detection with occlusion handling

Ouyang, W., & Wang, X. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition

Advanced Neural Network ApplicationsVideo Surveillance and Tracking Methods

Cited by 281

A Survey of Context Engineering for Large Language Models

Mei, L., Yao, J., Ge, Y., Wang, Y., Bi, B., Cai, Y., Liu, J., Li, M., Li, Z.-Z., Zhang, D., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 281

Spectre attacks: exploiting speculative execution

Kocher, P., Horn, J., Fogh, A., Genkin, D., Gruss, D., Haas, W., Hamburg, M., Lipp, M., Mangard, S., Prescher, T., et al. (2020) · Communications of the ACM

Security and Verification in ComputingCryptographic Implementations and Security

Cited by 281

Artificial intelligence in oncology: current applications and future perspectives

Luchini, C., Pea, A., & Scarpa, A. (2022) · British Journal of Cancer

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 281

SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities

Chen, B., Xu, Z., Kirmani, S., Ichter, B., Sadigh, D., Guibas, L., & Xia, F. (2024) · 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsAdvanced Neural Network Applications

Cited by 281

Spatio-Temporal Graph for Video Captioning With Knowledge Distillation

Pan, B., Cai, H., Huang, D.-A., Lee, K.-H., Gaidon, A., Adeli, E., & Niebles, J. C. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 281

An Efficient Image Encryption Scheme Based on the LSS Chaotic Map and Single S-Box

Lu, Q., Zhu, C., & Deng, X. (2020) · IEEE Access

Chaos-based Image/Signal EncryptionComputer Science and Engineering

Cited by 281

Evaluating the validity of volume-based and surface-based brain image registration for developmental cognitive neuroscience studies in children 4 to 11years of age

Ghosh, S. S., Kakunoori, S., Augustinack, J., Nieto-Castanon, A., Kovelman, I., Gaab, N., Christodoulou, J. A., Triantafyllou, C., Gabrieli, J. D. E., & Fischl, B. (2010) · NeuroImage

Medical Image Segmentation TechniquesFunctional Brain Connectivity Studies

Cited by 281

ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering

Yu, Z., Xu, D., Yu, J., Yu, T., Zhao, Z., Zhuang, Y., & Tao, D. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence

Multimodal Machine Learning ApplicationsHuman Pose and Action Recognition

Cited by 281

A Reference Model for Internet of Things Middleware

da Cruz, M. A. A., Rodrigues, J. J. P. C., Al-Muhtadi, J., Korotaev, V. V., & de Albuquerque, V. H. C. (2018) · IEEE Internet of Things Journal

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 281

Analyzing Adversarial Attacks against Deep Learning for Intrusion Detection in IoT Networks

Ibitoye, O., Shafiq, O., & Matrawy, A. (2019) · 2019 IEEE Global Communications Conference (GLOBECOM)

Network Security and Intrusion DetectionAdversarial Robustness in Machine Learning

Cited by 281