Results 51 to 60 of about 33,807 (240)
Multimodal Layer‐Crossing Interrogation of Brain Circuits Enabled by Microfluidic Axialtrodes
The study introduces a flexible microfluidic axialtrode that integrates optical, electrical, and chemical modalities within a single polymer fiber. By redistributing electrodes and fluidic channels along the fiber axis via angled cleaving, it enables simultaneous optogenetic stimulation, electrophysiological recording, and drug delivery across brain ...
Kunyang Sui +8 more
wiley +1 more source
In this paper, a specific type of incomplete data in Wi-Fi fingerprinting based indoor positioning systems (WF-IPS) is presented: censored and dropped mixture data. For fitting this type of data, a censored and dropped Gaussian Mixture Model (CD-GMM) was
Trung Kien Vu +2 more
doaj +1 more source
GMM-VRD: A Gaussian Mixture Model for Dealing With Virtual and Real Concept Drifts [PDF]
Concept drift is a change in the joint probability distribution of the problem. This term can be subdivided into two types: real drifts that affect the conditional probabilities p(y|x) or virtual drifts that affect the unconditional probability distribution p(x). Most existing work focuses on dealing with real concept drifts.
Gustavo H. F. M. Oliveira +2 more
openaire +1 more source
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Comparative Analysis of Audio Features for Unsupervised Speaker Change Detection
This study examines how ten different audio features, including MFCC, mel-spectrogram, chroma, and spectral contrast etc., influence speaker change detection (SCD) performance.
Alymzhan Toleu +4 more
doaj +1 more source
A Hybrid Hidden Markov Model for Pipeline Leakage Detection
In this paper, a deep neural network hidden Markov model (DNN-HMM) is proposed to detect pipeline leakage location. A long pipeline is divided into several sections and the leakage occurs in different section that is defined as different state of hidden ...
Mingchi Zhang, Xuemin Chen, Wei Li
doaj +1 more source
Fisher Vectors Derived from Hybrid Gaussian-Laplacian Mixture Models for Image Annotation [PDF]
In the traditional object recognition pipeline, descriptors are densely sampled over an image, pooled into a high dimensional non-linear representation and then passed to a classifier.
Klein, Benjamin +3 more
core
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu +5 more
wiley +1 more source
Droplet‐based microfluidics enables precise, high‐throughput microscale reactions but continues to face challenges in scalability, reproducibility, and data complexity. This review examines how artificial intelligence enhances droplet generation, detection, sorting, and adaptive control and discusses emerging opportunities for clinical and industrial ...
Junyan Lai +10 more
wiley +1 more source

