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Cross-centroid ripple pattern for facial expression recognition
In this paper, we propose a new feature descriptor Cross-Centroid Ripple Pattern (CRIP) for facial expression recognition. CRIP encodes the...
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Centroid-based graph matching networks for planar object tracking
Recently, keypoint-based methods have received more attention on planar object tracking due to their abilities to deal with partial noises, such as...
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A novel centroid based sentence classification approach for extractive summarization of COVID-19 news reports
A COVID-19 news covers subtopics like infections, deaths, the economy, jobs, and more. The proposed method generates a news summary based on the...
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Heterogeneous domain adaptation by class centroid matching and local discriminative structure preservation
Heterogeneous domain adaptation (HDA) aims at facilitating the target model training by leveraging knowledge from the heterogeneous source domain....
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Worddeepnet: handwritten gurumukhi word recognition using convolutional neural network
Deep learning models are considered a revolutionary learning paradigm in artificial intelligence and machine learning, piquing the interest of image...
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A Multi-task Network for Anatomy Identification in Endoscopic Pituitary Surgery
Pituitary tumours are in an anatomically dense region of the body, and often distort or encase the surrounding critical structures. This, in...
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Deep multi-view fuzzy k-means with weight allocation and entropy regularization
Multi-view clustering is a rapidly evolving research topic that exploits cross-view data obtained from different domains or modalities to describe...
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Learning cross-domain representations by vision transformer for unsupervised domain adaptation
Unsupervised Domain Adaptation (UDA) is a popular machine learning technique to reduce the distribution discrepancy among domains. Generally, most...
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An integration of meta-heuristic approach utilizing kernel principal component analysis for multimodal medical image registration
Medical image registration is vital for precise healthcare diagnosis, treatment planning, and disease progression tracking, but traditional methods...
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Auxiliary CNN for Graspability Modeling with 3D Point Clouds and Images for Robotic Gras**
Automatic object gras** is a challenging problem and has numerous applications in various fields. Currently, researchers have developed models that...
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Bee detection in bee hives using selective features from acoustic data
Honeybees, a key pollinator of the world’s most cultivated crops, are experiencing colony collapses due to a variety of factors. The existence of...
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A Two-Level Classifier for Prediction of Healthy and Unhealthy Lung Sounds Using Machine Learning and Convolutional Neural Network
The ability to detect lung disorders with the aid of lung sound auscultation has become very common these days. The early diagnose of these diseases...
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Discriminative Representation Learning for Cross-Domain Sentiment Classification
Cross-domain sentiment classification aims to solve the lack of labeled data in the target domain by using the knowledge of the source domain. Most...
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The Interactive Query Method with Clustering and Differential Privacy Protection Model Under Big Data Environment
To enhance the privacy protection as well as to improve data availability, a differential privacy data protection approach is proposed. Through big...
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Fast adaptive fuzzy enhancement and correlation features analysis of flame image of sintering section
The state of the sintering end point can be indirectly reflected by the flame image characteristics of the material layer section at the end of the...
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Few-Shot Classification with Contrastive Learning
A two-stage training paradigm consisting of sequential pre-training and meta-training stages has been widely used in current few-shot learning (FSL)...
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Shared Nearest Neighbor Calibration for Few-Shot Classification
Few-shot classification aims to classify query samples using very few labeled examples. Most existing methods follow the Prototypical Network to...
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Domain Incremental Learning for EEG-Based Seizure Prediction
When building seizure prediction systems, the typical research scenario is patient-specific. In this scenario, the model is limited to performing...
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SVFNeXt: Sparse Voxel Fusion for LiDAR-Based 3D Object Detection
Voxel-based 3D object detection methods have gained more popularity in autonomous driving. However, due to the sparse nature of LiDAR point clouds,...
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Automatic Landing Zone Plane Detection in Contrast-Enhanced Cardiac CT Volumes
Left atrial appendage closure (LAAC) is a common procedure whereby a device is implanted to prevent blood clots in the heart from entering the...