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Dual-branch and triple-attention network for pan-sharpening
Pan-sharpening is a technique used to generate high-resolution multi-spectral (HRMS) images by merging high-resolution panchromatic (PAN) images with...
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Knowledge and separating soft verbalizer based prompt-tuning for multi-label short text classification
Multi-label Short Text Classification (MSTC) is a challenging subtask of Multi-Label Text Classification (MLTC) for tagging a short text with the...
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HAMIATCM: high-availability membership inference attack against text classification models under little knowledge
Membership inference attack opens up a newly emerging and rapidly growing research to steal user privacy from text classification models, a core...
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A lightweight CNN-transformer model for learning traveling salesman problems
Several studies have attempted to solve traveling salesman problems (TSPs) using various deep learning techniques. Among them, Transformer-based...
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Predicting the robot's grip capacity on different objects using multi-object gras**
This study explores the novel concept of Multi-Object Gras** (MOG) and develops an architecture based on autoencoders and transformers for accurate...
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A binarization approach to model interactions between categorical predictors in Generalized Linear Models
In this paper, our goal is to enhance the interpretability of Generalized Linear Models by identifying the most relevant interactions between...
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Curriculum pre-training for stylized neural machine translation
Stylized neural machine translation (NMT) aims to translate sentences of one style into sentences of another style, it is essential for the...
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Nia-GNNs: neighbor-imbalanced aware graph neural networks for imbalanced node classification
It has been proven that Graph Neural Networks focus more on the majority class instances and ignore minority class instances when the class...
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RoDAL: style generation in robot calligraphy with deep adversarial learning
Generative art has drawn increased attention in recent AI applications. Traditional approaches of robot calligraphy have faced challenges in...
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Unsupervised deep learning for geometric feature detection and multilevel-multimodal image registration
Medical image registration is a crucial step in computer-assisted medical diagnosis, and has seen significant progress with the adoption of deep...
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Enhanced feature pyramid for multi-view stereo with adaptive correlation cost volume
AbstractMulti-level features are commonly employed in the cascade network, which is currently the dominant framework in multi-view stereo (MVS)....
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Will senior adults accept being cognitively assessed by a conversational agent? a user-interaction pilot study
AbstractBackground: early detection of dementia and Mild Cognitive Impairment (MCI) have an utmost significance nowadays, and smart conversational...
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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...
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RPV-CASNet: range-point-voxel integration with channel self-attention network for lidar point cloud segmentation
Maximizing the advantages of different views and mitigating their respective disadvantages in fine-grained segmentation tasks are an important...
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A lightweight convolutional swin transformer with cutmix augmentation and CBAM attention for compound emotion recognition
Facial emotion recognition has become a complicated task due to individual variations in facial characteristics, as well as racial and cultural...
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MPF-Net: multi-projection filtering network for few-shot object detection
Deep learning-based object detection has made tremendous progress in the field of intelligent vision systems. However, one of its major complaints is...
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EpiRiskNet: incorporating graph structure and static data as prior knowledge for improved time-series forecasting
EpiRiskNet combines time-series data with graph and static information to enhance forecasting accuracy. This model features the SCI-Block for...
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Neural-network-based safe learning control for non-zero-sum differential games of nonlinear systems with asymmetric input constraints
This paper primarily investigates a neural-network-based safe control scheme for solving the optimal control problem of continuous-time (CT)...
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FMDADA: Federated multi-discriminative adversarial domain adaptation
Federated domain adaptation system aims to address the problem of domain shift in a federated learning (FL) framework, where knowledge learned from...
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Semi-supervised feature selection by minimum neighborhood redundancy and maximum neighborhood relevancy
In the realm of machine learning, feature selection emerges as a prevalent data preprocessing technique, playing a crucial role in enhancing model...
