AIMC Topic: Algorithms

Clear Filters Showing 13251 to 13260 of 28713 articles

Attention2majority: Weak multiple instance learning for regenerative kidney grading on whole slide images.

Medical image analysis
Deep learning consistently demonstrates high performance in classifying and segmenting medical images like CT, PET, and MRI. However, compared to these kinds of images, whole slide images (WSIs) of stained tissue sections are huge and thus much less ...

Deep Learning Approach to UAV Detection and Classification by Using Compressively Sensed RF Signal.

Sensors (Basel, Switzerland)
Recently, the frequent occurrence of the misuse and intrusion of UAVs has made it a research challenge to identify and detect them effectively, and relatively high bandwidth and pressure on data transmission and real-time processing exist when sampli...

Improved Artificial Neural Network with State Order Dataset Estimation for Brain Cancer Cell Diagnosis.

BioMed research international
Brain cancer is one of the cell synthesis diseases. Brain cancer cells are analyzed for patient diagnosis. Due to this composite cell, the conceptual classifications differ from each and every brain cancer investigation. In the gene test, patient pro...

Deep Possibilistic -means Clustering Algorithm on Medical Datasets.

Computational and mathematical methods in medicine
In the past, the possibilistic -means clustering algorithm (PCM) has proven its superiority on various medical datasets by overcoming the unstable clustering effect caused by both the hard division of traditional hard clustering models and the suscep...

A Novel Approach of Feature Space Reconstruction with Three-Way Decisions for Long-Tailed Text Classification.

Computational intelligence and neuroscience
Text classification is widely studied by researchers in the natural language processing field. However, real-world text data often follow a long-tailed distribution as the frequency of each class is typically different. The performance of current mai...

MVGCNMDA: Multi-view Graph Augmentation Convolutional Network for Uncovering Disease-Related Microbes.

Interdisciplinary sciences, computational life sciences
MOTIVATION: Exploring the interrelationships between microbes and disease can help microbiologists make decisions and plan treatments. Predicting new microbe-disease associations currently relies on biological experiments and domain knowledge, which ...

An efficient model selection for linear discriminant function-based recursive feature elimination.

Journal of biomedical informatics
Model selection is an important issue in support vector machine-based recursive feature elimination (SVM-RFE). However, performing model selection on a linear SVM-RFE is difficult because the generalization error of SVM-RFE is hard to estimate. This ...

A Tightly Coupled LiDAR-Inertial SLAM for Perceptually Degraded Scenes.

Sensors (Basel, Switzerland)
Realizing robust six degrees of freedom (6DOF) state estimation and high-performance simultaneous localization and mapping (SLAM) for perceptually degraded scenes (such as underground tunnels, corridors, and roadways) is a challenge in robotics. To s...

Musical Instrument Identification Using Deep Learning Approach.

Sensors (Basel, Switzerland)
The work aims to propose a novel approach for automatically identifying all instruments present in an audio excerpt using sets of individual convolutional neural networks (CNNs) per tested instrument. The paper starts with a review of tasks related t...

Deep Reinforcement Learning for Resource Management on Network Slicing: A Survey.

Sensors (Basel, Switzerland)
Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving 5G and 6G networks. A 5G/6G network can comprise various network slices from unique or multiple tenants. Network providers need to perform intelligent and efficien...