2,081 Result(s)
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Cross-Architecture Knowledge Distillation
The Transformer network architecture has gained attention due to its ability to learn global relations and its superior performance. To boost performance, it is natural to distill complementary knowledge from ...
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CMEFS: chaotic map**-based mayfly optimization with fuzzy entropy for feature selection
Swarm intelligence algorithms availably settle the issue of feature selection for classification, whereas the Mayfly Optimization Algorithm (MOA) proposed in recent years has the superiority of high precision,...
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CD-iNet: Deep Invertible Network for Perceptual Image Color Difference Measurement
Image color difference (CD) measurement, a crucial concept in color science and imaging technology, aims to quantify the perceived difference between two colors. Most widely recognized CD formulae are recommen...
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Open AccessRetraction Note: Using hardware counter-based performance model to diagnose scaling issues of HPC applications
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Multi-source-free Domain Adaptive Object Detection
To enhance the transferability of object detection models in real-world scenarios where data is sampled from disparate distributions, considerable attention has been devoted to domain adaptive object detection...
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Towards Unified Defense for Face Forgery and Spoofing Attacks via Dual Space Reconstruction Learning
Real-world face recognition systems are vulnerable to diverse face attacks, ranging from digitally manipulated artifacts to physically crafted spoofing attacks. Existing works primarily focus on using an image...
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Open AccessGraph neural networks for text classification: a survey
Text Classification is the most essential and fundamental problem in Natural Language Processing. While numerous recent text classification models applied the sequential deep learning technique, graph neural n...
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Improved optimal foraging algorithm for global optimization
The optimal foraging algorithm (OFA) is a swarm-based algorithm motivated by animal behavioral ecology theory. When solving complex optimization problems characterized by multiple peaks, OFA is easy to get tra...
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Multi-example query over ontology-label knowledge graphs
Multi-example query over knowledge graphs allows users to provide multiple example fragments to express their intention, overcoming the shortage of single example query asks users to give a specific complete q...
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Luminance domain-guided low-light image enhancement
Images captured under low-light conditions often suffer from low contrast, high noise, and uneven brightness due to nightlight, backlight, and shadow. These challenges make it difficult to use them as high-qua...
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Open AccessPrimitiveNet: decomposing the global constraints for referring segmentation
In referring segmentation, modeling the complicated constraints in the multimodal information is one of the most challenging problems. As the information in a given language expression and image becomes increa...
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Graph analysis using a GPU-based parallel algorithm: quantum clustering
The article introduces a new method for applying Quantum Clustering to graph structures. Quantum Clustering (QC) is a density-based unsupervised learning method that determines cluster centers by constructing ...
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Open AccessEquilibrium optimizer-based harmony search algorithm with nonlinear dynamic domains and its application to real-world optimization problems
Harmony Search (HS) algorithm is a swarm intelligence algorithm inspired by musical improvisation. Although HS has been applied to various engineering problems, it faces challenges such as getting trapped in l...
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3D shape classification based on global and local features extraction with collaborative learning
It is important to extract both global and local features for view-based 3D shape classification. Therefore, we propose a 3D shape classification method based on global and local features extraction with colla...
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Towards Non Co-occurrence Incremental Object Detection with Unlabeled In-the-Wild Data
Deep networks have shown remarkable results in the task of object detection. However, their performance suffers critical drops when they are subsequently trained on novel classes without any sample from the ba...
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NeuralGLS: learning to guide local search with graph convolutional network for the traveling salesman problem
The traveling salesman problem (TSP) aims to find the shortest tour that visits each node of a given graph exactly once. TSPs have significant importance as numerous practical problems can be naturally formula...
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BDNet: a method based on forward and backward convolutional networks for action recognition in videos
Human action recognition analyzes the behavior in a scene according to the spatiotemporal features carried in image sequences. Existing works suffers from ineffective spatial–temporal feature learning. For sho...
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CSDG-FAS: Closed-Space Domain Generalization for Face Anti-spoofing
Domain generalization based Face Anti-spoofing (FAS) aims to enhance its ability to work in unseen domains. Existing methods endeavor to extract a discriminative common space through the alignment of distribut...
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Open AccessLCTCS: Low-Cost and Two-Channel Sparse Network for Hyperspectral Image Classification
Using convolutional neural networks (CNNs) in classifying hyperspectral images (HSIs) has achieved quite good results in recent years. It is widely used in agricultural remote sensing, geological exploration, ...
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A feature aggregation network for contour detection inspired by complex cells properties
Biological vision mechanism plays a very important role in detecting object contour information, so the research of bio-inspired contour detection has attracted widespread attention. In the visual physiologica...
