AIMC Topic: Algorithms

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Unsupervised Cross Domain Person Re-Identification by Multi-Loss Optimization Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Unsupervised cross domain (UCD) person re-identification (re-ID) aims to apply a model trained on a labeled source domain to an unlabeled target domain. It faces huge challenges as the identities have no overlap between these two domains. At present,...

HOReID: Deep High-Order Mapping Enhances Pose Alignment for Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Despite the remarkable progress in recent years, person Re-Identification (ReID) approaches frequently fail in cases where the semantic body parts are misaligned between the detected human boxes. To mitigate such cases, we propose a novel High-Order ...

Complementary Pseudo Labels for Unsupervised Domain Adaptation On Person Re-Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
In recent years, supervised person re-identification (re-ID) models have received increasing studies. However, these models trained on the source domain always suffer dramatic performance drop when tested on an unseen domain. Existing methods are pri...

Giant Panda Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The lack of automatic tools to identify giant panda makes it hard to keep track of and manage giant pandas in wildlife conservation missions. In this paper, we introduce a new Giant Panda Identification (GPID) task, which aims to identify each indivi...

Condition-Aware Comparison Scheme for Gait Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
As an important and challenging problem, gait recognition has gained considerable attention. It suffers from confounding conditions, that is, it is sensitive to camera views, dressing types and so on. Interestingly, it is observed that, under differe...

IMI-Bigpicture: A Central Repository for Digital Pathology.

Toxicologic pathology
To address the challenges posed by large-scale development, validation, and adoption of artificial intelligence (AI) in pathology, we have constituted a consortium of academics, small enterprises, and pharmaceutical companies and proposed the BIGPICT...

Performance and efficiency of machine learning algorithms for analyzing rectangular biomedical data.

Laboratory investigation; a journal of technical methods and pathology
Most biomedical datasets, including those of 'omics, population studies, and surveys, are rectangular in shape and have few missing data. Recently, their sample sizes have grown significantly. Rigorous analyses on these large datasets demand consider...

A Comparative Survey of Feature Extraction and Machine Learning Methods in Diverse Acoustic Environments.

Sensors (Basel, Switzerland)
Acoustic event detection and analysis has been widely developed in the last few years for its valuable application in monitoring elderly or dependant people, for surveillance issues, for multimedia retrieval, or even for biodiversity metrics in natur...

Conservation machine learning: a case study of random forests.

Scientific reports
Conservation machine learning conserves models across runs, users, and experiments-and puts them to good use. We have previously shown the merit of this idea through a small-scale preliminary experiment, involving a single dataset source, 10 datasets...

RNA secondary structure prediction using deep learning with thermodynamic integration.

Nature communications
Accurate predictions of RNA secondary structures can help uncover the roles of functional non-coding RNAs. Although machine learning-based models have achieved high performance in terms of prediction accuracy, overfitting is a common risk for such hi...