Results 81 to 90 of about 9,169,616 (322)

Klasifikasi Gagal Jantung menggunakan Metode SVM (Support Vector Machine)

Komputika
Gagal jantung merupakan penyakit mematikan nomor satu di dunia. Menurut data WHO (World Health Organization) dan WHF (World Heart Federation), pada tahun 2025 diperkirakan penyakit jantung akan menjadi penyebab utama kematian di negara-negara Asia ...
Laili Nur Farida, Saiful Bahri
doaj   +1 more source

DIAGNOSA PENYAKIT SALURAN PERNAPASAN DENGAN MENGGUNAKAN SUPPORT VECTOR MACHINE (SVM)

Barekeng, 2015
Support Vector Machine (SVM) telah banyak digunakan untuk membantu menyelesaikan berbagai macam permasalahan dalam rangka pengambilan keputusan berdasarkan pelatihan yang diberikan. Aplikasi SVM dapat diterapkan dalam berbagai bidang, salah satunya dalam
Zeth A. Leleury, Berny P. Tomasouw
doaj   +1 more source

Hate Speech Detection Using Support Vector Machine (SVM) Method

, 2023
Hate speech is a linguistic phenomenon that deviates from the norms and polite grammar in language and communication ethics. This research is aimed at detecting a word or sentence containing or not containing a hate speech using the SVM method for classification. This research takes data using the Tweepy API and gets a total sample data of 1681.
Mohammad Attar Jibran, Ade Eviyanti
openaire   +2 more sources

Detection of coronavirus Disease (COVID-19) based on Deep Features and Support Vector Machine

International journal of mathematical, engineering and management sciences, 2020
The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected
Dr. Prabira Kumar Sethy, S. Behera, P. K. Ratha, Preesat Biswas   +3 more
semanticscholar   +1 more source

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

A new fuzzy support vector machine with pinball loss

Discover Artificial Intelligence, 2023
The fuzzy support vector machine (FSVM) assigns each sample a fuzzy membership value based on its relevance, making it less sensitive to noise or outliers in the data.
Ram Nayan Verma, Rahul Deo, Rakesh Srivastava, Naidu Subbarao, Gajendra Pratap Singh   +4 more
doaj   +1 more source

Flexible Sensors for Robotics Tactile Perception: A Review

Advanced Robotics Research, EarlyView.
Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley   +1 more source

Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery

Italian National Conference on Sensors, 2017
In previous classification studies, three non-parametric classifiers, Random Forest (RF), k-Nearest Neighbor (kNN), and Support Vector Machine (SVM), were reported as the foremost classifiers at producing high accuracies. However, only a few studies have
Noi Thanh Phan, M. Kappas
semanticscholar   +1 more source

Bio‐Inspired Object Retrieval via Proximity‐Guided Adaptive Thigmotactic Exploration and Neuromorphic Recognition

Advanced Robotics Research, EarlyView.
Sparse active‐infrared proximity sensing is coupled to an adaptive thigmotactic controller for camera‐inaccessible object retrieval. After grasping, receptor‐informed encoding transforms force, temperature, and wrist force–torque signals into spike trains for spiking neural network recognition.
Fengyi Wang, Nitish Thakor, Gordon Cheng
wiley   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

Advanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown, Mathilda Avirett‐Mackenzie, Carolin Villforth, Georgios Exarchakis   +3 more
wiley   +1 more source