Results 71 to 80 of about 61,624 (324)

Low-Complexity Vector Quantized Compressed Sensing via Deep Neural Networks

IEEE Open Journal of the Communications Society, 2020
Sparse signals, encountered in many wireless and signal acquisition applications, can be acquired via compressed sensing (CS) to reduce computations and transmissions, crucial for resource-limited devices, e.g., wireless sensors.
Markus Leinonen, Marian Codreanu
doaj   +1 more source

KOMPARASI HASIL KLASIFIKASI PENYAKIT DIABETES MELLITUS MENGGUNAKAN JARINGAN SYARAF TIRUAN BACKPROPAGATION DAN LEARNING VECTOR QUANTIZATION [PDF]

, 2011
Diabetes Milletus merupakan penyakit yang ditandai dengan kenaikan kadar gula dalam darah. Penyebab penyakit ini biasanya disebabkan destruksi sel beta, kebiasaan pola makan, dan olah raga yang kurang teratur. Menurut asuhan keperawatan diabetes mellitus
Agus, Nurkhozin, Imam, Mukhlas, Mohammad Isa, Irawan   +2 more
core  

Online Product Quantization

, 2018
Approximate nearest neighbor (ANN) search has achieved great success in many tasks. However, existing popular methods for ANN search, such as hashing and quantization methods, are designed for static databases only.
Tsang, Ivor W., Xu, Donna, Zhang, Ying
core   +1 more source

Machine Learning‐Assisted Infectious Disease Detection in Low‐Income Areas: Toward Rapid Triage of Dengue and Zika Virus Using Open‐Source Hardware

Advanced Intelligent Discovery, EarlyView.
This study introduces an affordable machine learning platform for simultaneous dengue and zika detection using fluorine‐doped tin oxide thin films modified with gold nanoparticles and DNA aptamers. Designed for low‐cost, hardware‐limited devices (< $25), the model achieves 95.3% accuracy and uses only 9.4 kB of RAM, demonstrating viability for resource‐
Marina Ribeiro Batistuti Sawazaki, Bassam Bachour Junior, Marcelo Mulato, José Ilton de Oliveira Filho   +3 more
wiley   +1 more source

SISTEM VERIFIKASI WAJAH MENGGUNAKAN JARINGAN SARAF TIRUAN LEARNING VECTOR QUANTIZATION

Jurnal Informatika, 2010
Verifikasi wajah merupakan salah satu teknologi biometrika yang menjadi perhatian para peneliti. Banyak sekali sistem aplikasi yang berbasis kepada verifikasi wajah misalnya: akses pintu, akses mesin ATM, sistem presensi kehadiran, dll.
Abdul Fadlil, Surya Yeki
doaj   +1 more source

KLASIFIKASI RUMAH LAYAK HUNI DI KABUPATEN BREBES DENGAN MENGGUNAKAN METODE LEARNING VECTOR QUANTIZATION DAN NAIVE BAYES [PDF]

, 2016
House is a very basic need for everyone besides food and clothing. House can reflect the level of welfare and the level of health of its inhabitants. The advisability of a house as a good shelter can be seen from the structure and facilities of buildings.
SIMATUPANG, FITRI JUNIATY
core  

Deep Learning‐Assisted Coherent Raman Scattering Microscopy

Advanced Intelligent Discovery, EarlyView.
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, Rujia Liu, Xinyan Zhang, Xun Chen, Shuhua Yue   +4 more
wiley   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Unsupervised Kernel Learning Vector Quantization [PDF]

Advanced Engineering Forum, 2012
In this paper, we propose an unsupervised kernel learning vector quantization (UKLVQ) algorithm that combines the concepts of the kernel method and traditional unsupervised learning vector quantization (ULVQ). We first use the definition of the shadow kernel to give a general representation of the UKLVQ method and then easily implement the UKLVQ ...
openaire   +1 more source

Adaptive Metric Learning Vector Quantization for Ordinal Classification [PDF]

Neural Computation, 2012
Many pattern analysis problems require classification of examples into naturally ordered classes. In such cases, nominal classification schemes will ignore the class order relationships, which can have a detrimental effect on classification accuracy.
Fouad, Shereen, Tino, Peter
openaire   +2 more sources