AIMC Topic: Databases, Factual

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Exploiting Multiple Optimizers with Transfer Learning Techniques for the Identification of COVID-19 Patients.

Journal of healthcare engineering
Due to the rapid spread of COVID-19 and its induced death worldwide, it is imperative to develop a reliable tool for the early detection of this disease. Chest X-ray is currently accepted to be one of the reliable means for such a detection purpose. ...

Distant Supervision Relation Extraction via adaptive dependency-path and additional knowledge graph supervision.

Neural networks : the official journal of the International Neural Network Society
Relation Extraction systems train an extractor by aligning relation instances in Knowledge Base with a large amount of labeled corpora. Since the labeled datasets are very expensive, Distant Supervision Relation Extraction (DSRE) utilizes rough corpu...

Modality independent adversarial network for generalized zero shot image classification.

Neural networks : the official journal of the International Neural Network Society
Zero Shot Learning (ZSL) aims to classify images of unseen target classes by transferring knowledge from source classes through semantic embeddings. The core of ZSL research is to embed both visual representation of object instance and semantic descr...

EventEpi-A natural language processing framework for event-based surveillance.

PLoS computational biology
According to the World Health Organization (WHO), around 60% of all outbreaks are detected using informal sources. In many public health institutes, including the WHO and the Robert Koch Institute (RKI), dedicated groups of public health agents sift ...

Moving targets in drug discovery.

Scientific reports
Drug Discovery is a lengthy and costly process and has faced a period of declining productivity within the last two decades resulting in increasing importance of integrative data-driven approaches. In this paper, data mining and integration is levera...

Identification of prognostic factors for pediatric myocarditis with a random forests algorithm-assisted approach.

Pediatric research
BACKGROUND: Pediatric myocarditis is a rare disease with substantial mortality. Little is known regarding its prognostic factors. We hypothesize that certain comorbidities and procedural needs may increase risks of poor outcomes. This study aims to i...

Joint Local and Global Information Learning With Single Apex Frame Detection for Micro-Expression Recognition.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Micro-expressions (MEs) are rapid and subtle facial movements that are difficult to detect and recognize. Most recent works have attempted to recognize MEs with spatial and temporal information from video clips. According to psychological studies, th...

Hierarchical Paired Channel Fusion Network for Street Scene Change Detection.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Street Scene Change Detection (SSCD) aims to locate the changed regions between a given street-view image pair captured at different times, which is an important yet challenging task in the computer vision community. The intuitive way to solve the SS...

Hier R-CNN: Instance-Level Human Parts Detection and A New Benchmark.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Detecting human parts at instance-level is an essential prerequisite for the analysis of human keypoints, actions, and attributes. Nonetheless, there is a lack of a large-scale, rich-annotated dataset for human parts detection. We fill in the gap by ...

Automatic classification and segmentation of single-molecule fluorescence time traces with deep learning.

Nature communications
Traces from single-molecule fluorescence microscopy (SMFM) experiments exhibit photophysical artifacts that typically necessitate human expert screening, which is time-consuming and introduces potential for user-dependent expectation bias. Here, we u...