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Hierarchical Patch Aggregation Transformer for Motion Deblurring
The encoder-decoder framework based on Transformer components has become a paradigm in the field of image deblurring architecture design. In this...
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Medical image super-resolution via transformer-based hierarchical encoder–decoder network
Medical image super-resolution (SR) has emerged as an effective means to enhance the resolution of medical images. Nevertheless, many existing...
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Correspondence between Hierarchical Knowledge Classifiers
AbstractHierarchical, descriptive, and faceted methods of constructing knowledge classifiers and also the classification of knowledge using...
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HGADC: Hierarchical Genetic Algorithm with Density-Based Clustering for TSP
Genetic algorithms (GA) are widely used to solve complex combinatorial optimization problems, such as the Traveling Salesman Problem (TSP). However,...
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Simple hierarchical PageRank graph neural networks
Graph neural networks (GNNs) have many variants for graph representation learning. Several works introduce PageRank into GNNs to improve its...
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Hierarchical modal interaction balance cross-modal hashing for unsupervised image-text retrieval
As multimedia technologies advance, untagged image-text data processing has become central in cross-modal retrieval. However, current methods often...
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Hierarchical Bayesian Optimization Algorithm
The previous chapter has discussed how hierarchy can be used to reduce problem complexity in black-box optimization. Additionally, the chapter has...
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Classification with costly features in hierarchical deep sets
Classification with costly features (CwCF) is a classification problem that includes the cost of features in the optimization criteria. Individually...
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Parallelism-Based Session Creation to Identify High-Level Activities in Event Log Abstraction
Process mining utilizes event data to gain insights into the execution of processes. While techniques are valuable, their effectiveness may be...
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Hierarchical Neural Network with Serial Attention Mechanism for Review Sentiment Classifification
Hierarchical neural networks have achieved success in review sentiment classification. Recently, some works achieved improvements by integrating user...
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Learning Hierarchical Planning-Based Policies from Offline Data
Hierarchical policy architectures incorporating some planning component into the top-level have shown superior performance and generalization in...
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Learning-based correspondence classifier with self-attention hierarchical network
Finding valid correspondences is of considerable significance to image matching, which has been regarded as the key of numerous vision-based tasks....
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A Hierarchical Theme Recognition Model for Sandplay Therapy
Sandplay therapy functions as a pivotal tool for psychological projection, where testers construct a scene to mirror their inner world while...
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Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering
Spatial statistics often involves Cholesky decomposition of covariance matrices. To ensure scalability to high dimensions, several recent...
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Hierarchical reinforcement learning for kinematic control tasks with parameterized action spaces
Most existing reinforcement learning (RL) algorithms are solely applied to scenarios with pure discrete action space or pure continuous action space....
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An energy-efficient hierarchical data fusion approach in IoT
Data Fusion (DF) involves merging data from various heterogeneous sources to generate fused data that is reduced in volume while preserving its...
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HLC: hierarchically-aware label correlation for hierarchical text classification
AbstractHierarchical Text Classification (HTC) leverages the hierarchical structure of labels to enhance text categorization. Existing methods use a...
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Multi-modal hierarchical fusion network for fine-grained paper classification
Because huge amount of scientific papers have been published at an accelerating rate, it is beneficial to do intelligent paper classification,...
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High-Level Decision-Making Non-player Vehicles
Availability of realistic driver models, also able to represent various driving styles, is key to add traffic in serious games on automotive driving....
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Hierarchical reinforcement learning for handling sparse rewards in multi-goal navigation
Reinforcement learning (RL) has achieved remarkable advancements in navigation tasks in recent years. However, tackling multi-goal navigation tasks...
