Results 101 to 110 of about 323,408 (293)

Beyond the Norm: Unsupervised Anomaly Detection in Telecommunications with Mahalanobis Distance

Computers
Anomaly Detection (AD) in telecommunication networks is critical for maintaining service reliability and performance. However, operational networks present significant challenges: high-dimensional Key Performance Indicator (KPI) data collected from ...
Aline Mefleh, Michal Patryk Debicki, Ali Mubarak, Maroun Saade, Nathanael Weill   +4 more
doaj   +1 more source

Intelligent Orthopedics: Machine Learning in Diagnosis of Bone Disease, Implants, and Bone Health Monitoring

Advanced Healthcare Materials, EarlyView.
Efficient recovery from traumatic or degenerative diseases is a great challenge, even after all the advancements in bone and cartilage regeneration. Machine learning (ML) algorithms have presented opportunities to enhance these aspects by accurately analyzing imaging data.
Maryam Kamaei, Hesam Mohammadi, Shamim Golafshan, Mojtaba Alehosseini, Mahsa Mohammadzadeh, Atefeh Golshirazi, Nasim Golafshan, Tatiane Eufrásio‐da‐Silva, Alireza Dolatshahi‐Pirouz, Gorka Orive   +9 more
wiley   +1 more source

Towards Robust Hyperspectral Target Detection via Test-Time Spectrum Adaptation

Remote Sensing
Target detection is a cornerstone task in hyperspectral image processing but faces significant challenges due to domain gaps. While statistical detectors like Constrained Energy Minimization (CEM) and Adaptive Cosine Estimator (ACE) are not prone to ...
Robin Gerster, Peter Stütz
doaj   +1 more source

Representational Bias in Unsupervised Learning of Syllable Structure [PDF]

, 2005
Unsupervised learning algorithms based on Expectation Maximization (EM) are often straightforward to implement and provably converge on a local likelihood maximum. However, these algorithms often do not perform well in practice.
Johnson, Mark, Sharon Goldwater, Mark Johnson, Goldwater, Sharon; id_orcid   +3 more
core   +1 more source

Engineered Microvascular Model of the Blood–Brain–Tumor Barrier Reveals Endothelial Remodeling in Diffuse Midline Glioma

Advanced Healthcare Materials, EarlyView.
We developed a patient‐derived, functional microfluidic model of the diffuse midline glioma (DMG) blood–brain–tumor barrier (BBTB) comprised of endothelial cells, astrocytes, pericytes, and tumor cells. The system forms perfusable microvasculature, reveals the BBTB retains vascular integrity, identifies DMG‐specific transcriptomic changes distinct from
Kimberly R. Bennett, Yann S. Vanrobaeys, Tessy Teboh, Zakiya Smith, Anderson Scott, Cynthia Hajal, Paula T. Hammond, Joelle P. Straehla   +7 more
wiley   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Unsupervised Tree Detection from UAV Imagery and 3D Point Clouds via Distance Transform-Based Circle Estimation and AIC Optimization

Remote Sensing
This work proposes a novel tree detection methodology, named DTCD (Distance Transform Circle Detection), based on a fast circle detection method via Distance Transform and Akaike Information Criterion (AIC) optimization. More specifically, a visible-band
Smaragda Markaki, Costas Panagiotakis
doaj   +1 more source

Unsupervised Ensemble Regression

CoRR, 2017
Consider a regression problem where there is no labeled data and the only observations are the predictions $f_i(x_j)$ of $m$ experts $f_{i}$ over many samples $x_j$. With no knowledge on the accuracy of the experts, is it still possible to accurately estimate the unknown responses $y_{j}$? Can one still detect the least or most accurate experts?
Omer Dror, Boaz Nadler, Erhan Bilal, Yuval Kluger   +3 more
openaire   +2 more sources

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

UMLN: Open-World Object Detection Empowered by Unsupervised Modeling and Location-Enhanced Network

Tsinghua Science and Technology
Open-world object detection (OWOD) is a challenging task requiring models to detect both known and unknown objects while incrementally learning from new data.
Yangyang Huang, Jie Hu, Ronghua Luo
doaj   +1 more source