Results 41 to 50 of about 442,254 (313)

A Comparative Study between SVM and Fuzzy Inference System for the Automatic Prediction of Sleep Stages and the Assessment of Sleep Quality

EAI Endorsed Transactions on Pervasive Health and Technology, 2015
This paper compares two supervised learning algorithms for predicting the sleep stages based on the human brain activity. The first step of the presented work regards feature extraction from real human electroencephalography (EEG) data together with its ...
John Gialelis, Chris Panagiotou, Ioakeim Samaras, Petros Chondros, Dimitris Karadimas   +4 more
doaj   +1 more source

EEG-induced Fear-type Emotion Classification Through Wavelet Packet Decomposition, Wavelet Entropy, and SVM

Hittite Journal of Science and Engineering, 2022
Among the most significant characteristics of human beings is their ability to feel emotions. In recent years, human-machine interface (HM) research has centered on ways to empower the classification of emotions.
Ahmet Ergun Gümüş, Çağlar Uyulan, Zozan Güleken   +2 more
doaj   +1 more source

Weed Detection Using SVMs [PDF]

Engineering, Technology & Applied Science Research, 2018
The major concern in Pakistani agriculture is the reduction of growing weed. This research aims to provide a weed detection tool for future agri-robots. The weed detection tool incorporates the use of machine-learning procedure explicitly implementing Support Vector Machines (SVMs) and blob analysis for the effective classification of crop and weed ...
Sadia Murawwat, Abuzar Qureshi, Shahriar Ahmad, Yousaira Shahid   +3 more
openaire   +1 more source

SVM-Based Channel Estimation and Data Detection for One-Bit Massive MIMO systems [PDF]

, 2020
The use of low-resolution Analog-to-Digital Converters (ADCs) is a practical solution for reducing cost and power consumption for massive Multiple-Input-Multiple-Output (MIMO) systems.
Nguyen, DHN, Nguyen, LV, Swindlehurst, AL   +2 more
core   +2 more sources

Micropatterned Biphasic Printed Electrodes for High‐Fidelity on‐Skin Bioelectronics

Advanced Functional Materials, EarlyView.
Micropatterned biphasic printed electrodes achieve unprecedented skin conformity and low impedance by combining liquid‐metal droplets with microstructured 3D lattices. This scalable approach enables high‐fidelity detection of ECG, EMG, and EEG signals, including alpha rhythms from the forehead, with long‐term comfort and stability.
Manuel Reis Carneiro, Telmo Lopes, André F. Silva, Carmel Majidi, Mahmoud Tavakoli   +4 more
wiley   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

A Divide-and-Conquer Solver for Kernel Support Vector Machines [PDF]

, 2013
The kernel support vector machine (SVM) is one of the most widely used classification methods; however, the amount of computation required becomes the bottleneck when facing millions of samples.
Dhillon, Inderjit S., Hsieh, Cho-Jui, Si, Si   +2 more
core   +1 more source

Computer-aided diagnosis of lung nodule using gradient tree boosting and Bayesian optimization

, 2017
We aimed to evaluate computer-aided diagnosis (CADx) system for lung nodule classification focusing on (i) usefulness of gradient tree boosting (XGBoost) and (ii) effectiveness of parameter optimization using Bayesian optimization (Tree Parzen Estimator,
Kojima, Ryosuke, Kuroda, Tomohiro, Nishio, Mizuho, Nishizawa, Mitsuo, Sugiyama, Osamu, Togashi, Kaori, Yakami, Masahiro   +6 more
core   +2 more sources

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Sensing-aware kernel SVM [PDF]

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014
We propose a novel approach for designing kernels for support vector machines (SVMs) when the class label is linked to the observation through a latent state and the likelihood function of the observation given the state (the sensing model) is available.
Ding, Weicong, Ishwar, Prakash, Saligrama, Venkatesh, Karl, W. Clem   +3 more
openaire   +2 more sources