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Discriminative feature encoding for intrinsic image decomposition
Intrinsic image decomposition is an important and long-standing computer vision problem. Given an input image, recovering the physical scene...
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Encoding learning network combined with feature similarity constraints for human action recognition
Extreme learning machine (ELM) is a fast and efficient classifier. Due to the inability to process descriptor-level features extracted from video...
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Encoding feature set information in heterogeneous graph neural networks for game provenance
AbstractGame Provenance has been proposed and employed for Game Analytics tasks as they capture game session data in detail and allow exploratory...
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MGFEEN: a multi-granularity feature encoding ensemble network for remote sensing image classification
Deep convolutional neural networks (DCNNs) have emerged as powerful tools in diverse remote sensing domains, but their optimization remains...
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EFECL: Feature encoding enhancement with contrastive learning for indoor 3D object detection
Good proposal initials are critical for 3D object detection applications. However, due to the significant geometry variation of indoor scenes,...
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Anomaly Detection Using Feature Encoding and Trajectory Association on Edge Devices for Residential Video Surveillance
In recent years, intelligent surveillance becomes one of the most important community services for residential societies. Intelligent surveillance...
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Adversarial Active Learning with Guided BERT Feature Encoding
Recent advances in BERT-based models has significantly improved the performance of many applications on text data, such as text classification,...
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Feature Encoding by Location-Enhanced Word2Vec Embedding for Human Activity Recognition in Smart Homes
Human Activity Recognition (HAR) in Smart Homes (SH) is the basis of providing automatic and comfortable living experience for occupants, especially...
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Multi-spectral Dynamic Feature Encoding Network for Image Demoiréing
Moiré often appears when photographing textured objects, which can seriously degrade the quality of the captured photos. Due to the wide distribution...
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Enhancing software model encoding for feature location approaches based on machine learning techniques
Feature location is one of the main activities performed during software evolution. In our previous works, we proposed an approach for feature...
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Neural News Recommendation with Interactive News Encoding and Mixed User Encoding
Personalized news recommendation is of great significance in hel** users find news of interest. In the task of news recommendation, the main point...
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A rule-based protein classification approach using normalized distance-based encoding method
Protein classification is a burgeoning field in biological data mining, underscoring the importance of devising effective feature extraction methods....
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Progressive encoding-decoding image dehazing network
In this paper, we propose a progressive encoding-decoding network (PEDN) for image dehazing. First, we built a basic dehaze unit to progressively...
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Feature learning and encoding for multi-script writer identification
Writer identification from handwriting samples has been an interesting research problem for the pattern recognition community in general and...
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Time series data encoding in Apache IoTDB: comparative analysis and recommendation
Not only the vast applications but also the distinct features of time series data stimulate the booming growth of time series database management...
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Position information encoding FPN for small object detection in aerial images
Small object detection in aerial images is a challenge in remote sensing. Recently, convolutional neural networks (CNNs) have succeeded by learning...
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Optimizing IoT intrusion detection system: feature selection versus feature extraction in machine learning
Internet of Things (IoT) devices are widely used but also vulnerable to cyberattacks that can cause security issues. To protect against this, machine...
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Machine learning-based intrusion detection: feature selection versus feature extraction
Internet of Things (IoTs) has been playing an important role in many sectors, such as smart cities, smart agriculture, smart healthcare, and smart...
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Multi-feature self-attention super-resolution network
In recent years, single-image super-resolution (SISR) methods based on the attention mechanism have been widely explored and achieved remarkable...
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Feature ranking based consensus clustering for feature subset selection
Feature subset selection problem is an NP hard problem and there is a need for computationally efficient algorithms that find near optimal feature...
