Results 41 to 50 of about 57,218 (285)

Learning vector quantization neural network–based model reference adaptive control method for intelligent lower-limb prosthesis

Advances in Mechanical Engineering, 2016
This article focuses on the design of a control system for intelligent prostheses. Learning vector quantization neural network–based model reference adaptive control method is employed to implement real-time trajectory tracking and damp torque control of
Jia-Qiang Yang, Lei Yang, Yuliang Ma
doaj   +1 more source

Convergence of Stochastic Vector Quantization and Learning Vector Quantization with Bregman Divergences

IFAC-PapersOnLine, 2020
Abstract Stochastic vector quantization methods have been extensively studied in supervised and unsupervised learning problems as online, data-driven, interpretable, robust, and fast to train and evaluate algorithms. Being prototype-based methods, they depend on a dissimilarity measure, which is both necessary and sufficient to belong to the family ...
Christos N. Mavridis, John S. Baras
openaire   +2 more sources

Learning Vector Quantization 3 (LVQ3) and Spatial Fuzzy C-Means (SFCM) for Beef and Pork Image Classification [PDF]

, 2018
Base on some cases in Indonesia, meat sellers often mix beef and pork. Indonesia is a predominantly Muslim country. Pork is forbidden in Islam. In this research, the classification of beef and pork image was performed.
Jasril, J. (Jasril), Sanjaya, S. (Suwanto)   +1 more
core  

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source

Deteksi Penyakit Diabetes Retinopati Pada Retina Mata Berdasarkan Pengolahan Citra

JuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2017
Diabetic Retinopathy is a disease that strikes the retina of the eye in patients who have diabetes mellitus. Medical examination against sufferers of Diabetic Retinopathy is done with observation directly by eye surgeons. In this case, eye retinal images
Adri Pramana Putra Putra, Youllia Indrawaty Nurhasanah, Andriana Zulkarnain   +2 more
doaj   +1 more source

Penerapan Metode Learning Vector Quantization (LVQ) untuk Mendeteksi Penyalahgunaan Narkoba

Contemporary Mathematics and Applications (ConMathA), 2021
Dalam penelitian ini, metode LVQ akan diterapkan untuk mendeteksi penyalahgunaan narkoba berdasarkan gejala-gejala yang dialami seseorang. Untuk mendapatkan tingkat akurasi terbaik, maka data pelatihan dan data pengujian dibagi ke dalam tiga skema ...
Berny Pebo Tomasouw, Salmon Notje Aulele, Monalisa E. Rijoly   +2 more
doaj   +1 more source

Combined compression and classification with learning vector quantization [PDF]

IEEE Transactions on Information Theory, 1999
Summary: Combined compression and classification problems are becoming increasingly important in many applications with large amounts of sensory data and large sets of classes. These applications range from automatic target recognition (ATR) to medical diagnosis, speech recognition, and fault detection and identification in manufacturing systems.
Baras, John S., Dey, Subhrakanti
openaire   +5 more sources

Machine‐Learning‐Aided Advanced Electrochemical Biosensors

Advanced Materials, EarlyView.
Electrochemical biosensors are highly sensitive, portable, and versatile. Advanced nanomaterials enhance their performance, while machine learning (ML) improves data analysis, minimizes interference, and optimizes sensor design. Despite progress in both fields, their combined potential in diagnostics remains underexplored.
Andrei Bocan, Roozbeh Siavash Moakhar, Carolina del Real Mata, Max Petkun, Tristan De Iure‐Grimmel, Sripadh Guptha Yedire, Hamed Shieh, Arash Khorrami Jahromi, Sahar Sadat Mahshid, Sara Mahshid   +9 more
wiley   +1 more source

Lightweight Road Environment Segmentation using Vector Quantization [PDF]

ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Road environment segmentation plays a significant role in autonomous driving. Numerous works based on Fully Convolutional Networks (FCNs) and Transformer architectures have been proposed to leverage local and global contextual learning for efficient and ...
J. Kwag, A. Yilmaz, C. Toth
doaj   +1 more source

AI‐Driven Defect Engineering for Advanced Thermoelectric Materials

Advanced Materials, EarlyView.
This review presents how AI accelerates the design of defect‐tuned thermoelectric materials. By integrating machine learning with high‐throughput data and physics‐informed representations, it enables efficient prediction of thermoelectric performance from complex defect landscapes.
Chu‐Liang Fu, Mouyang Cheng, Nguyen Tuan Hung, Eunbi Rha, Zhantao Chen, Ryotaro Okabe, Denisse Córdova Carrizales, Manasi Mandal, Yongqiang Cheng, Mingda Li   +9 more
wiley   +1 more source