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AIPR' 2021: Applied Imagery Pattern Recognition

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截稿日期:
2021-08-15
通知日期:
会议日期:
2021-10-12
会议地点:
Washington DC, USA
届数:
50
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征稿

AIPR' 2021 (Applied Imagery Pattern Recognition) is an academic conference held in Washington DC, USA on 2021-10-12. The paper submission deadline is 2021-08-15.

The purpose of the Applied Imagery Pattern Recognition (AIPR) annual workshops is to bring together researchers from government, industry, and academia in an elegant setting conducive to technical interchange across a broad range of disciplines. The papers span a range of topics, from research to fielded systems and provide to scientists, developers, and managers alike, a broad vision of the applicability of image analysis and machine learning technologies. AIPR continues the half-century of success and tradition in pioneering new topics in applied image and visual understanding. The current worldwide pandemic focuses our collective attention on artificial intelligence (AI) in medicine and biomedicine to improve healthcare. Healthcare systems around the world are being challenged and experiencing a large influx of patients requiring intensive monitoring. Researchers are working on near-term and long-term projects to bring relief to clinical providers with enhanced automation capability to assist in patient monitoring, rapid diagnosis, and drug discovery. Large medical databases are offering new opportunities to accelerate the adoption of AI and improve medical outcomes. The 2021 IEEE AIPR Workshop will explore artificial intelligence in medicine, healthcare, and neuroscience. In addition to papers on regular AIPR topics in applied imagery, the Workshop Committee invites papers that address all aspects of medical and biomedical AI, development of novel tools, methodologies, algorithms, theory, and mechanisms for biomedicine, healthcare, and neuroscience. Theme topics include, but are not limited to, the following: AI-based medical imaging for COVID-19 detection, outcome prediction, or monitoring Deep learning and AI for medicine, computer aided diagnosis, biology, drug discovery Medical image classification, segmentation, and registration Connectomics, brain imaging, fMRI, neural circuitry, neuropathologies Multiscale biological and biomedical signal and image analysis Deep neural networks for pathology, radiology, and microscopy Robotics technologies for medical and biomedical applications Biomedical analysis for clinical imaging and informatics Data mining and image retrieval for biomedical imagery Personalized healthcare, electronic health records, translational and precision medicine Geospatial epidemiology and healthcare Pattern recognition for early identification of viral contagions Patient monitoring, wearable devices, and multi-sensor multimodal diagnostics Regional healthcare lessons learned in pandemics Advances in statistical image processing Novel uses of differentiable programming in developing AI systems Ubiquitous sensors and their impact on biomedical measurements Conducting medical imaging science with urgency
由 Dou Sun 最后更新于

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CCF全称影响因子出版商ISSN
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