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301
Regional-to-Local Point-Voxel Transformer for Large-Scale Indoor 3D Point Cloud Semantic Segmentation
Published 2023-10-01“…The window-based point-voxel branch concentrates on local feature learning while integrating voxel-level information within each window. …”
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302
Graph neural network recommendation algorithm based on improved dual tower model
Published 2024-02-01“…Additionally, this method utilizes graph convolutional networks for higher-order feature learning, pooling the node embeddings of the twin towers to obtain enhanced end-user and item representations. …”
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303
Feature Refine Network for Salient Object Detection
Published 2022-06-01“…Different feature learning strategies have enhanced performance in recent deep neural network-based salient object detection. …”
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304
Semi-Supervised Machine Condition Monitoring by Learning Deep Discriminative Audio Features
Published 2021-10-01“…We propose a comprehensive feature learning approach that operates on raw audio, by supervising the formation of salient audio embeddings in latent states of a deep temporal convolutional neural network. …”
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305
An Improved Informer Model for Short-Term Load Forecasting by Considering Periodic Property of Load Profiles
Published 2022-08-01“…In recent times, an attention-based model, Informer, has been proposed for efficient feature learning of lone sequences. To solve the quadratic complexity of traditional method, this model designs what is called ProbSparse self-attention mechanism. …”
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306
Learning representations for human re-identification
Published 2017“…The goal of this thesis is to present various feature learning architectures in different perspectives to tackle the aforementioned challenges in human re-identification. …”
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Thesis -
307
Combining wav2vec 2.0 Fine-Tuning and ConLearnNet for Speech Emotion Recognition
Published 2024-03-01“…ConLearnNet comprises three steps: feature learning, contrastive learning, and classification. …”
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308
Network Embedding Algorithm Taking in Variational Graph AutoEncoder
Published 2022-02-01“…This algorithm first pre-processes the attribute features, i.e., the attribute feature learning of the network nodes. Then, the feature learning matrix and the adjacency matrix of the network are fed into the variational graph autoencoder algorithm to obtain the Gaussian distribution of the potential vectors, which more easily generate high-quality node embedding representation vectors. …”
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309
EXAM: A Framework of Learning Extreme and Moderate Embeddings for Person Re-ID
Published 2021-01-01“…This is done using discriminative feature learning, requiring attention-based guidance during training. …”
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310
Sentiment Interaction Distillation Network for Image Sentiment Analysis
Published 2022-03-01“…In addition, we propose a knowledge distillation framework to utilize interaction information guiding global context feature learning, which can avoid noisy features introduced by error propagation and a varying number of objects. …”
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311
A dual-branch multi-feature deep fusion network framework for hyperspectral image classification
Published 2024-02-01“…For the second part, a series spectral-spatial feature learning modules and augmentation modules for spatial feature learning are being developed to learn these features in a continuous manner while also effectively fusing features from various depth layers. …”
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312
Text3D: 3D Convolutional Neural Networks for Text Classification
Published 2023-07-01“…This paper proposes a simple, yet effective, approach for hierarchy feature learning using 3D CNN in text classification tasks, named Text3D. …”
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313
Multi-view learning-based heterogeneous network representation learning
Published 2023-12-01“…Firstly, to simplify the difficulty of feature learning, a novel view generation strategy is designed to divide the heterogeneous network into multiple sub-views that contain only one semantic feature and its related structural features. …”
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314
Integrating Enhanced Sparse Autoencoder-Based Artificial Neural Network Technique and Softmax Regression for Medical Diagnosis
Published 2020-11-01“…Hence, the proposed approach has the advantage of effective feature learning and robust classification performance. …”
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315
Predicting Adverse Drug Reactions from Social Media Posts: Data Balance, Feature Selection and Deep Learning
Published 2022-03-01“…In contrast to the traditional machine learning methods, our feature learning approach can automatically achieve the required task to save the manual effort for the large number of experiments.…”
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316
Deep Error-Correcting Output Codes
Published 2023-12-01“…We have conducted extensive experiments to compare DeepECOCs with traditional ECOC, feature learning and deep learning algorithms. The results demonstrate that DeepECOCs perform, not only better than existing ECOC and feature learning algorithms, but also related to deep learning ones in most cases.…”
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317
Lightweight Semantic-Guided Neural Networks Based on Single Head Attention for Action Recognition
Published 2022-11-01“…However, because an SGN focuses on global feature learning rather than local feature learning owing to the structural characteristics, there is a limit to an action recognition in which the dependency between neighbouring nodes is important. …”
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318
Improved Heart Disease Prediction Using Particle Swarm Optimization Based Stacked Sparse Autoencoder
Published 2021-09-01“…The optimization by the PSO improves the feature learning and classification performance of the SSAE. …”
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319
Object detection utilizing modified auto encoder and convolutional neural networks
Published 2018“…The proposed method has two main advantages over other unsupervised feature learning techniques. Firstly, as it will be shown, features are detected with a much higher precision. …”
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Conference or Workshop Item -
320
Exploring Channel Properties to Improve Singing Voice Detection with Convolutional Neural Networks
Published 2021-12-01“…Because of the poor adaptability and complexity of feature engineering, there is a recent trend towards feature learning in which deep neural networks play the roles of feature extraction and classification. …”
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