Results 51 to 60 of about 5,483,449 (298)

Deep Learning and Music Adversaries [PDF]

, 2015
OA Monitor ExerciseOA Monitor ExerciseAn {\em adversary} is essentially an algorithm intent on making a classification system perform in some particular way given an input, e.g., increase the probability of a false negative.
STURM, BLT, Kereliuk, C, Kereliuk, Corey Mose, Sturm, Bob L., Larsen, Jan, Larsen, J   +5 more
core   +1 more source

Experimental Study on Long Short-term Memory Networks for Identifying P-wave Primary Phase

CT Lilun yu yingyong yanjiu
Identifying primary phases of seismic waveforms is a routine task in seismic data processing. Owing to the low efficiency of manual identification and the influence of human subjective factors, many methods for the automatic identification of the primary
Tianzhe WANG, Wanji ZHANG, Shanbo QI, Guoming JIANG   +3 more
doaj   +1 more source

A Deep Neural Network Model for Speaker Identification

Applied Sciences, 2021
Speaker identification is a classification task which aims to identify a subject from a given time-series sequential data. Since the speech signal is a continuous one-dimensional time series, most of the current research methods are based on ...
Feng Ye, Jun Yang
doaj   +1 more source

SF-ICNN: Spectral–Fractal Iterative Convolutional Neural Network for Classification of Hyperspectral Images [PDF]

One primary concern in the field of remote-sensing image processing is the precise classification of hyperspectral images (HSIs). Lately, deep-learning models have demonstrated cutting-edge results in HSI classification.
Akbari, Vahid, Behnam Asghari Beirami, Mehran Alizadeh Pirbasti, Alizadeh Pirbasti, Mehran, Asghari Beirami, Behnam, Vahid Akbari   +5 more
core   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

Radar emitter signal recognition based on one-dimensional convolutional recurrent neural network

四川大学学报. 自然科学版, 2023
Aiming at the problem of incomplete features and low timeliness in artificial extraction of radar emitter signal, a novel recognition method is proposed based on one-dimension convolutional neural network and bidirectional gated recurrent unit.
LIU Tao-Tao, TIAN Chun-Jin, PU Yun-Wei, GUO Jiang   +3 more
doaj  

Architecture‐Driven Functional Coupling in Vertically Aligned Nanocomposites

Advanced Functional Materials, EarlyView.
Vertically aligned nanocomposites define a growth‐engineered architecture in which vertical interfaces, strain fields, defect pathways, and phase connectivity are created simultaneously. This review shows how these architectural features couple ferroic, optical, ionic, electrochemical, and device responses, establishing design rules and open challenges
Md Shatil Islam‐Shanto, Javier Zamudio‐García, Abraham Sánchez‐Caballero, David Marrero‐López, Vincenzo Esposito   +4 more
wiley   +1 more source

A novel framework for cryptocurrency price forecasting: integrating dual attention mechanisms, genetic algorithm feature selection, and Hybrid Adam-PSO optimization

Cogent Engineering
This paper proposes a robust framework for cryptocurrency price forecasting by integrating technical indicators, genetic algorithm based feature selection, and hybrid deep learning models. Technical indicators capture historical patterns, while a genetic
Susrita Mahapatro, Prabhat Kumar Sahu, Asit Kumar Subudhi   +2 more
doaj   +1 more source

Hand Gesture Recognition in Video Sequences Using Deep Convolutional and Recurrent Neural Networks

Applied Computer Systems, 2020
Deep learning is a new branch of machine learning, which is widely used by researchers in a lot of artificial intelligence applications, including signal processing and computer vision.
Obaid Falah, Babadi Amin, Yoosofan Ahmad
doaj   +1 more source