A Systematic Review Protocol “Beyond Diagnostic Accuracy: Calibration and Predictive Uncertainty of Artificial Intelligence Models for Oral and Dental Disease Diagnosis” Title of the ReviewBeyond Diagnostic Accuracy: Calibration and Predictive Uncertainty of Artificial Intelligence Models for Oral and Dental Disease Di...
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
Code, per-run results, tables and figures for the manuscript "Communication-efficient split federated learning for patient-independent ECG classification". The ECG databases are not included.
Venkatesh Janarthanan, Viswanathan A· Zenodo (CERN European Organi...· 0 citations
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
Reach audiences
Advertise in front of researchers, engineers, and readers.
Re-created code for the PLoS One article e0322749 (2025): nuclei segmentation (SegNet) and classification (DenseNet121) on PanNuke with Hyperband tuning, TensorFlow Lite quantization and federated learning. Includes the result tables underlying the reproduced results.
Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin et al.· Zenodo (CERN European Organi...· 0 citations
A median filter removes impulsive noise by sorting a few neighbouring samples and picking the middle one. Filters of this family (rank-order or order-statistic filters) need no multiplications, cannot be thrown off by a few wild samples, and their output never moves more than their input does. They were popular in the...
Juan Carlos del Rio Romero· Zenodo (CERN European Organi...· 0 citations
The proliferation of multi-cloud architectures has intensified challenges in phishing detection, as security intelligence becomes fragmented across heterogeneous cloud infrastructures governed by stringent privacy regulations and data sovereignty constraints. Conventional centralized threat detection paradigms necessit...
Shakir Khan, Arvind Panwar, Achin Jain et al.· Scientific Reports· 0 citations
Re-created code for the PLoS One article e0322749 (2025): nuclei segmentation (SegNet) and classification (DenseNet121) on PanNuke with Hyperband tuning, TensorFlow Lite quantization and federated learning. Includes the result tables underlying the reproduced results.
Anjir Ahmed Chowdhury, S M Hasan Mahmud, Md Palash Uddin et al.· Zenodo (CERN European Organi...· 0 citations
Résumé (FR) Ce document, produit avec l'assistance de Gemini 3 Raisonnement, est publié sous licence Apache 2.0. Il constitue une publication défensive volontaire (antériorité) entrant dans l'état de la technique selon les législations applicables (EPC Art. 54(2); French IPC Art. L 611-11; cf. 35 U.S.C. §102(a)). Face...
Xavier Pillet· Zenodo (CERN European Organi...· 0 citations
The integration of machine learning (ML) into Internet of Things (IoT) systems presents transformative opportunities across various domains but also introduces numerous security challenges. This study explores the role of ML in enhancing IoT functionalities, particularly in data analytics, security, optimization, and u...
Kamel-Dine Haouam, Mourad Benmalek· International Journal of Inf...· 0 citations
Privacy-preserving machine learning in Vehicular Ad Hoc Networks (VANETs) must address sensitive on-board data, limited ground-truth annotations, and verifiable model-update integrity. This paper proposes ZK-FL, a decentralized federated learning framework for Intelligent Transportation Systems (ITS) scene classificati...
M. Medvei, Miruna-Mihaela Modiga, Iulian Aciobăniței et al.· Frontiers in Future Transpor...· 0 citations
Accurate 3D delineation of bone tumors and metastatic lesions from volumetric CT is essential for diagnosis, staging, radiotherapy planning, and treatment monitoring, yet manual contouring is time consuming and variable across observers. Although modern 3D CNN/Transformer segmenters achieve strong centralized performan...
Yongan Liu, Tao Yu, Dan Su et al.· Scientific Reports· 0 citations
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
MIT News · Artificial Intelligence· news.mit.eduOct 13, 2026
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 7, 2026
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
