AIMC Journal:
IEEE transactions on pattern analysis and machine intelligence

Showing 171 to 180 of 300 articles

Viewport-Based CNN: A Multi-Task Approach for Assessing 360° Video Quality.

IEEE transactions on pattern analysis and machine intelligence Mar 4, 2022
For 360° video, the existing visual quality assessment (VQA) approaches are designed based on either the whole frames or the cropped patches, ignoring the fact that subjects can only access viewports. When watching 360° video, subjects select viewpor...
Humans Neural Networks, Computer Algorithms Eye Movements Motion Head Movements
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Adversarial Joint-Learning Recurrent Neural Network for Incomplete Time Series Classification.

IEEE transactions on pattern analysis and machine intelligence Mar 4, 2022
Incomplete time series classification (ITSC) is an important issue in time series analysis since temporal data often has missing values in practical applications. However, integrating imputation (replacing missing data) and classification within a mo...
Neural Networks, Computer Algorithms Time Factors
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Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation.

IEEE transactions on pattern analysis and machine intelligence Mar 4, 2022
Domain adaptation, which transfers the knowledge from label-rich source domain to unlabeled target domains, is a challenging task in machine learning. The prior domain adaptation methods focus on pairwise adaptation assumption with a single source an...
Machine Learning Algorithms Semantics
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Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Recognizing multiple labels of an image is a practical yet challenging task, and remarkable progress has been achieved by searching for semantic regions and exploiting label dependencies. However, current works utilize RNN/LSTM to implicitly capture ...
Neural Networks, Computer Machine Learning Algorithms Semantics
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Efficient and Stable Graph Scattering Transforms via Pruning.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Graph convolutional networks (GCNs) have well-documented performance in various graph learning tasks, but their analysis is still at its infancy. Graph scattering transforms (GSTs) offer training-free deep GCN models that extract features from graph ...
Neural Networks, Computer Algorithms Learning
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Multi-Task Learning With Coarse Priors for Robust Part-Aware Person Re-Identification.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Part-level representations are important for robust person re-identification (ReID), but in practice feature quality suffers due to the body part misalignment problem. In this paper, we present a robust, compact, and easy-to-use method called the Mul...
Humans Algorithms Databases, Factual Deep Learning Pedestrians
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Generative Imputation and Stochastic Prediction.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
In many machine learning applications, we are faced with incomplete datasets. In the literature, missing data imputation techniques have been mostly concerned with filling missing values. However, the existence of missing values is synonymous with un...
Machine Learning Algorithms
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Semantic Object Accuracy for Generative Text-to-Image Synthesis.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Generative adversarial networks conditioned on textual image descriptions are capable of generating realistic-looking images. However, current methods still struggle to generate images based on complex image captions from a heterogeneous domain. Furt...
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Semantics
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Building and Interpreting Deep Similarity Models.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Many learning algorithms such as kernel machines, nearest neighbors, clustering, or anomaly detection, are based on distances or similarities. Before similarities are used for training an actual machine learning model, we would like to verify that th...
Neural Networks, Computer Machine Learning Algorithms Cluster Analysis
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Meta-Transfer Learning Through Hard Tasks.

IEEE transactions on pattern analysis and machine intelligence Feb 3, 2022
Meta-learning has been proposed as a framework to address the challenging few-shot learning setting. The key idea is to leverage a large number of similar few-shot tasks in order to learn how to adapt a base-learner to a new task for which only a few...
Neural Networks, Computer Machine Learning Algorithms Learning
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