Check computer science papers: citations, claims and retractions

Multi-scale phase-based local features

Carneiro, G., & Jepson, A. D. (2003) · 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.

Advanced Image and Video Retrieval TechniquesImage Retrieval and Classification Techniques

Cited by 104

Explaining Outliers by Subspace Separability

Micenkova, B., Ng, R. T., Dang, X.-H., & Assent, I. (2013) · 2013 IEEE 13th International Conference on Data Mining

Anomaly Detection Techniques and ApplicationsAdvanced Statistical Methods and Models

Cited by 104

Blockchain technology in the smart city: A bibliometric review

Rejeb, A., Rejeb, K., Simske, S. J., & Keogh, J. G. (2022) · Quality & Quantity

Blockchain Technology Applications and SecuritySmart Cities and Technologies

Cited by 104

FaceTube: predicting personality from facial expressions of emotion in online conversational video

Biel, J.-I., Teijeiro-Mosquera, L., & Gatica-Perez, D. (2012) · Proceedings of the 14th ACM international conference on Multimodal interaction

Emotion and Mood RecognitionFace recognition and analysis

Cited by 104

BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning

Chevalier-Boisvert, M., Bahdanau, D., Lahlou, S., Willems, L., Saharia, C., Nguyen, T. H., & Bengio, Y. (2018) · arXiv

Reinforcement Learning in RoboticsNatural Language Processing Techniques

Cited by 104

Artificial intelligence-based semantic internet of things in a user-centric smart city

Guo, K., Lu, Y., Gao, H., & Cao, R. (2018) · Sensors

IoT and Edge/Fog ComputingInternet of Things and AI

Cited by 104

An Interface and Algorithms for Authenticated Encryption

McGrew, D. (2008)

Cryptographic Implementations and SecurityAdvanced Authentication Protocols Security

Cited by 104

Opal: Multimodal Image Generation for News Illustration

Liu, V., Qiao, H., & Chilton, L. (2022) · Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology

Digital Media and Visual ArtGenerative Adversarial Networks and Image Synthesis

Cited by 104

Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages

Li, Y., Li, J., Lin, W., & Li, J. (2018) · arXiv

Advanced Neural Network ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 104

FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

Shah, J., Bikshandi, G., Zhang, Y., Thakkar, V., Ramani, P., & Dao, T. (2024) · arXiv

Parallel Computing and Optimization TechniquesAdvanced Neural Network Applications

Cited by 104

Investigating the link between transaction and computational costs in a blockchain environment

Jabbar, A., & Dani, S. (2020) · International Journal of Production Research

Blockchain Technology Applications and SecurityBlockchain Technology in Education and Learning

Cited by 104

On the Importance of Stereo for Accurate Depth Estimation: An Efficient Semi-Supervised Deep Neural Network Approach

Smolyanskiy, N., Kamenev, A., & Birchfield, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

Advanced Vision and ImagingAdvanced Neural Network Applications

Cited by 104

Effect of a Deep Learning Framework-Based Computer-Aided Diagnosis System on the Diagnostic Performance of Radiologists in Differentiating between Malignant and Benign Masses on Breast Ultrasonography

Choi, J. S., Han, B.-K., Ko, E. S., Bae, J. M., Ko, E. Y., Song, S. H., Kwon, M.-R., Shin, J. H., & Hahn, S. Y. (2019) · Korean Journal of Radiology

AI in cancer detectionBreast Lesions and Carcinomas

Cited by 104

A Feature Extraction Method Based on Differential Entropy and Linear Discriminant Analysis for Emotion Recognition

Chen, D.-W., Miao, R., Yang, W.-Q., Liang, Y., Chen, H.-H., Huang, L., Deng, C.-J., & Han, N. (2019) · Sensors

Emotion and Mood RecognitionEEG and Brain-Computer Interfaces

Cited by 104

LLM+P: Empowering Large Language Models with Optimal Planning Proficiency

Liu, B., Jiang, Y., Zhang, X., Liu, Q., Zhang, S., Biswas, J., & Stone, P. (2023) · arXiv

AI-based Problem Solving and PlanningNatural Language Processing Techniques

Cited by 104

Improving Noise Robust Automatic Speech Recognition with Single-Channel Time-Domain Enhancement Network

Kinoshita, K., Ochiai, T., Delcroix, M., & Nakatani, T. (2020) · ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Speech and Audio ProcessingSpeech Recognition and Synthesis

Cited by 104

Exploring and Unleashing the Power of Large Language Models in Automated Code Translation

Yang, Z., Liu, F., Yu, Z., Keung, J. W., Li, J., Liu, S., Hong, Y., Ma, X., Jin, Z., & Li, G. (2024) · Proceedings of the ACM on Software Engineering

Software Engineering ResearchNatural Language Processing Techniques

Cited by 104

HuntGPT: Integrating Machine Learning-Based Anomaly Detection and Explainable AI with Large Language Models (LLMs)

Ali, T., Kostakos, P., & Sheikhi, S. (2026) · Telecom

Network Security and Intrusion DetectionExplainable Artificial Intelligence (XAI)

Cited by 104

Hyperspectral Image Unmixing With Endmember Bundles and Group Sparsity Inducing Mixed Norms

Drumetz, L., Meyer, T. R., Chanussot, J., Bertozzi, A. L., & Jutten, C. (2019) · IEEE Transactions on Image Processing

Remote-Sensing Image ClassificationSparse and Compressive Sensing Techniques

Cited by 104

A Generic Quality Control Framework for Fetal Ultrasound Cardiac Four-Chamber Planes

Dong, J., Liu, S., Liao, Y., Wen, H., Lei, B., Li, S., & Wang, T. (2020) · IEEE Journal of Biomedical and Health Informatics

Medical Image Segmentation TechniquesArtificial Intelligence in Healthcare and Education

Cited by 104

Rethink reporting of evaluation results in AI

Burnell, R., Schellaert, W., Burden, J., Ullman, T. D., Martinez-Plumed, F., Tenenbaum, J. B., Rutar, D., Cheke, L. G., Sohl-Dickstein, J., Mitchell, M., et al. (2023) · Science

Ethics and Social Impacts of AIScientific Computing and Data Management

Cited by 104

Trust in artificial Intelligence: a five country study

Gillespie, N., Lockey, S., & Curtis, C. (2021) · The University of Queensland

Ethics and Social Impacts of AIHuman-Automation Interaction and Safety

Cited by 104

Information Perspective to Probabilistic Modeling: Boltzmann Machines versus Born Machines

Cheng, S., Chen, J., & Wang, L. (2018) · Entropy

Neural Networks and ApplicationsQuantum Computing Algorithms and Architecture

Cited by 104

A simple model for the immune network.

Parisi, G. (1990) · Proceedings of the National Academy of Sciences

Artificial Immune Systems ApplicationsT-cell and B-cell Immunology

Cited by 104