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921
Geoscience-aware deep learning: A new paradigm for remote sensing
Published 2022-06-01“…Although DL models have powerful feature learning and representation capabilities, traditional DL has inherent problems including working as a black box and generally requiring a large number of labeled training data. …”
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922
Sistem Isyarat Bahasa Indonesia (SIBI) Metode Convolutional Neural Network Sequential secara Real Time
Published 2022-08-01“…Teknologi visi komputer deep learning convolutional neural network (CNN) digunakan untuk feature learning dan mengklasifikasi isyarat tangan pada sebuah obyek. …”
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923
Robust Speech Emotion Recognition Using CNN+LSTM Based on Stochastic Fractal Search Optimization Algorithm
Published 2022-01-01“…This deep learning model consists of a convolutional neural network (CNN) composed of four local feature-learning blocks and a long short-term memory (LSTM) layer for learning local and long-term correlations in the log Mel-spectrogram of the input speech samples. …”
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924
Forest Fire Segmentation via Temporal Transformer from Aerial Images
Published 2023-03-01“…Then, we used a transformer to perform deep temporal-feature extraction, which enhanced the feature learning of the fire pixels and made the feature extraction more robust. …”
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925
Brain and Nature-Inspired Learning, Computation and Recognition /
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software, multimedia -
926
Construction and improvement of English vocabulary learning model integrating spiking neural network and convolutional long short-term memory algorithm.
Published 2024-01-01“…By adding information transfer and interaction modules, the feature learning and the timing information processing are optimized to improve the vocabulary learning ability of the model in different text contents. …”
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927
Deep-HPI-pred: An R-Shiny applet for network-based classification and prediction of Host-Pathogen protein-protein interactions
Published 2024-12-01“…In the framework of current study, we developed a web-based R/Shiny app, Deep-HPI-pred, that uses network-driven feature learning method to predict the yet unmapped interactions between pathogen and host proteins. …”
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928
Soft-masks guided faster region-based convolutional neural network for domain adaptation in wind turbine detection
Published 2023-01-01“…The predominant approaches to alleviate the domain discrepancy are adversarial feature learning strategies, which focus on feature alignment for style (e.g., color, texture, illumination, etc.) gaps without considering the content (e.g., densities, backgrounds, and layout scenes) gaps. …”
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929
Label-Free White Blood Cell Classification Using Refractive Index Tomography and Deep Learning
Published 2021-01-01“…Our results show >99% accuracy for the binary classification of myeloids and lymphoids and >96% accuracy for the four-type classification of B and T lymphocytes, monocyte, and myelocytes. The feature learning capability of our approach is visualized via an unsupervised dimension reduction technique. …”
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930
A Robust Heart Disease Prediction System Using Hybrid Deep Neural Networks
Published 2023-01-01“…The HDNN is employed to apply its feature learning capabilities and non-linear technology to capture complex patterns and relationships in HD datasets, leading to enhanced prediction accuracy. …”
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931
Swarm Intelligence with Deep Transfer Learning Driven Aerial Image Classification Model on UAV Networks
Published 2022-06-01“…The previous approach to the scene classification method depends on feature coding models with lower-level handcrafted features or unsupervised feature learning. The emergence of convolutional neural network (CNN) is developing image classification techniques more effectively. …”
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932
A Hybrid Model for Predicting the Environment Humidity of Pigeon Sheds
Published 2023-01-01“…First, the SG filter is used for data smoothing to remove abnormal noise in the data signal to enhance the feature learning ability of the prediction system. Next, the original data is selected through the PLS method to select information higher than the set threshold. …”
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933
LUCC Simulation Based on RF-CNN-LSTM-CA Model with High-Quality Seed Selection Iterative Algorithm
Published 2023-03-01“…In the traditional machine learning CA model, when using statistical methods to obtain neighborhood features, there is usually the problem that the spatio-temporal feature learning of neighborhood factors is insufficient. …”
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934
X3DFast model for classifying dairy cow behaviors based on a two-pathway architecture
Published 2023-11-01“…To address this, we developed an effective yet lightweight model for fast and accurate dairy cow behavior feature learning from video data. We focused on four common behaviors: standing, walking, lying, and mounting. …”
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935
DMSC-Net: A deep Multi-Scale context network for 3D object detection of indoor point clouds
Published 2023-08-01“…The proposed end-to-end network, termed as DMSC-Net, consists of an indoor point cloud feature learning backbone (FLB) unit, and three modules, namely the DMSC, a voting decision (VD) module, and an MHA module. …”
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936
Domain Mapping and Deep Learning from Multiple MRI Clinical Datasets for Prediction of Molecular Subtypes in Low Grade Gliomas
Published 2020-07-01“…Finally, an efficient deep feature learning method, multi-stream convolutional autoencoder (CAE) and feature fusion, is proposed for the prediction of molecular subtypes (1p/19q-codeletion and IDH mutation). …”
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937
Detection of Corona Faults in Switchgear by Using 1D-CNN, LSTM, and 1D-CNN-LSTM Methods
Published 2023-03-01“…Recent years have seen the successful use of Deep Learning (DL) applications for corona and non-corona detection, owing to their autonomous feature learning capability. This paper systematically analyzes three deep learning techniques, namely 1D-CNN, LSTM, and 1D-CNN-LSTM hybrid models, to identify the most effective model for detecting corona faults. …”
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938
Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model
Published 2023-05-01“…To identify pharmacophenotypes, unsupervised machine learning analysis with automated feature learning using restricted Boltzmann machine and hierarchical clustering was performed on the medication administration records of each patient during the first 24 h of their ICU stay. …”
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939
AE-GAN-Net: Learning Invariant Feature Descriptor to Match Ground Camera Images and a Large-Scale 3D Image-Based Point Cloud for Outdoor Augmented Reality
Published 2019-09-01“…However, unlike real camera images, the rendered images from the 3D image-based point cloud are inevitably contaminated with image distortion, blurred resolution, and obstructions, which makes image matching with the handcrafted descriptors or existing feature learning neural networks very challenging. Thus, we first propose a novel end-to-end network, AE-GAN-Net, consisting of two AutoEncoders (AEs) with Generative Adversarial Network (GAN) embedding, to learn invariant feature descriptors for cross-domain image matching. …”
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940
A general-purpose organic gel computer that learns by itself
Published 2023-01-01“…Subsequently, synthesis alone solves classification, feature learning problems instantly with single shot training. …”
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