IEEE Transactions on Pattern Analysis and Machine Intelligence

Aims & Scope✦ Inferred from recent articles

This journal focuses on advancements in pattern analysis and machine intelligence. Recent articles explore techniques for large-scale unsupervised semantic segmentation using foundation models, graph condensation for efficient graph representation, and pseudo-labeling for semi-supervised multi-label learning. Other topics include light field image processing, hypergraph neural networks for complex relationship modeling, and enhancing text-to-image generation models. The journal also covers few-shot video action recognition, theoretical frameworks for fairness in deep learning, point cloud completion, and semantic segmentation model evaluation. Additionally, research on Bayes filters, long-video understanding with multimodal models, human-like cognitive mechanisms for visual question answering, federated learning, and affine correspondences for geometric problems are featured.

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Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Source: OpenAlex · Note: citations accumulate over time so older years appear higher

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Subject Classification