AIMC Topic: Neural Networks, Computer

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U-Net: deep learning for cell counting, detection, and morphometry.

Nature methods
U-Net is a generic deep-learning solution for frequently occurring quantification tasks such as cell detection and shape measurements in biomedical image data. We present an ImageJ plugin that enables non-machine-learning experts to analyze their dat...

Particulate Matter Exposure of Passengers at Bus Stations: A Review.

International journal of environmental research and public health
This review clarifies particulate matter (PM) pollution, including its levels, the factors affecting its distribution, and its health effects on passengers waiting at bus stations. The usual factors affecting the characteristics and composition of PM...

PASNet: pathway-associated sparse deep neural network for prognosis prediction from high-throughput data.

BMC bioinformatics
BACKGROUND: Predicting prognosis in patients from large-scale genomic data is a fundamentally challenging problem in genomic medicine. However, the prognosis still remains poor in many diseases. The poor prognosis may be caused by high complexity of ...

Automatic interpretation of otoliths using deep learning.

PloS one
The age structure of a fish population has important implications for recruitment processes and population fluctuations, and is a key input to fisheries-assessment models. The current method of determining age structure relies on manually reading age...

Using a stacked-autoencoder neural network model to estimate sea state bias for a radar altimeter.

PloS one
This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training data...

Micro-Net: A unified model for segmentation of various objects in microscopy images.

Medical image analysis
Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images. We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in microscopy i...

Artificial Intelligence-Based Grading Quality of Bovine Blastocyst Digital Images: Direct Capture with Juxtaposed Lenses of Smartphone Camera and Stereomicroscope Ocular Lens.

Sensors (Basel, Switzerland)
In this study, we developed an online graphical and intuitive interface connected to a server aiming to facilitate professional access worldwide to those facing problems with bovine blastocysts classification. The interface Blasto3Q, where 3Q refers ...

Asynchronous Multiplex Communication Channels in 2-D Neural Network With Fluctuating Characteristics.

IEEE transactions on neural networks and learning systems
Neurons behave like transistors, but have fluctuating characteristics. In this paper, we show that several asynchronous multiplex communication channels can be established in a 2-D mesh neural network with randomly generated weights between eight nei...