Results 61 to 70 of about 38,801 (275)

The balancing trick: Optimized sampling of imbalanced datasets—A brief survey of the recent State of the Art

Engineering Reports, 2021
This survey paper focuses on one of the current primary issues challenging data mining researchers experimenting on real‐world datasets. The problem is that of imbalanced class distribution that generates a bias toward the majority class due to ...
Dr. Seba Susan, Amitesh Kumar
doaj   +1 more source

DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks

, 2017
In this paper we develop a novel computational sensing framework for sensing and recovering structured signals. When trained on a set of representative signals, our framework learns to take undersampled measurements and recover signals from them using a ...
Baraniuk, Richard G., Dasarathy, Gautam, Mousavi, Ali   +2 more
core   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

Undersampling in Orthogonal Frequency Division Multiplexing Telecommunication Systems

Applied Sciences, 2014
Several techniques have been proposed that attempt to reconstruct a sparse signal from fewer samples than the ones required by the Nyquist theorem.
Nikos Petrellis
doaj   +1 more source

Identification of Clinically Relevant HIV Vif Protein Motif Mutations through Machine Learning and Undersampling

Cells, 2023
Human Immunodeficiency virus (HIV) and its clinical entity, the Acquired Immunodeficiency Syndrome (AIDS) continue to represent an important health burden worldwide.
José Salomón Altamirano-Flores, Luis Ángel Alvarado-Hernández, Juan Carlos Cuevas-Tello, Peter Tino, Sandra E. Guerra-Palomares, Christian A. Garcia-Sepulveda   +5 more
doaj   +1 more source

Double Temporal Sparsity Based Accelerated Reconstruction in Compressed Sensing fMRI

, 2017
A number of reconstruction methods have been proposed recently for accelerated functional Magnetic Resonance Imaging (fMRI) data collection. However, existing methods suffer with the challenge of greater artifacts at high acceleration factors. This paper
Aggarwal, Priya, Gupta, Anubha
core   +1 more source

Solving Data Overlapping Problem Using A Class‐Separable Extreme Learning Machine Auto‐Encoder

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The overlapping and imbalanced data in classification present key challenges. Class‐separable extreme learning machine auto‐encoding (CS‐ELM‐AE) is proposed, which is an enhancement of ELM‐AE that better handles overlapping data by clustering points from the same class together. Applying oversampling addresses imbalanced data.
Ekkarat Boonchieng, Wanchaloem Nadda
wiley   +1 more source

Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle

Journal of Applied Informatics and Computing
Heart disease is one of the leading causes of death in the world with risk factors such as atherosclerosis, high blood pressure, and smoking. Early diagnosis is essential to reduce mortality and improve patients' quality of life. This study evaluates the
Gusti Ayu Putu Febriyanti, Anna Baita
doaj   +1 more source

High‐Resolution Deep Learning Dixon Magnetic Resonance Imaging of the Sacroiliac Joints Is Noninferior to Standard Magnetic Resonance Imaging in Patients With Suspected Axial Spondyloarthritis

Arthritis &Rheumatology, EarlyView.
Objective To compare the multisequence standard magnetic resonance imaging (sMRI) protocol of the sacroiliac joints with a single high‐resolution deep learning–reconstructed Dixon sequence (DL‐Dixon) in patients with suspected axial spondyloarthritis (axSpA). Methods Seventy‐six patients with chronic low back pain and suspected axSpA underwent clinical,
Dominik Deppe, Mariam Koka, Fabian Proft, Sevtap Tugce Ulas, Kay‐Geert Hermann, Denis Poddubnyy, Mikhail Protopopov, Henriette Baum, Hildrun Haibel, Mehrgan Shahryari, Valeria Rios Rodriguez, Jens Vogel‐Claussen, Torsten Diekhoff   +12 more
wiley   +1 more source

Data Reduction in Phase-Sensitive OTDR with Ultra-Low Sampling Resolution and Undersampling Techniques

Sensors, 2022
Data storage is a problem that cannot be ignored in the long-term monitoring of a phase-sensitive optical time-domain reflectometry (Φ-OTDR) system. In this paper, we proposed a data-reduction approach for heterodyne Φ-OTDR using an ultra-low sampling ...
Feihong Yu, Liyang Shao, Shuaiqi Liu, Weijie Xu, Dongrui Xiao, Huanhuan Liu, Perry Ping Shum   +6 more
doaj   +1 more source