Deep Learning

A fundamental building block of any computer-assisted interventions (CAI) is the ability to automatically understand what the surgeons are performing throughout the surgery. In other words, recognizing the surgical activities being performed or the tools being used by the surgeon can be deemed as an essential steps toward CAI. The main motivation for these tasks is to design efficient solutions for surgical workflow analysis. The CATARACTS dataset was proposed in this context. This dataset consists of 50 cataract surgery.

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7233 Views

The LEDNet dataset consists of image data of a field area that are captured from a mobile phone camera.

Images in the dataset contain the information of an area where a PCB board is placed, containing 6 LEDs. Each state of the LEDs on the PCB board represents a binary number, with the ON state corresponding to binary 1 and the OFF state corresponding to binary 0. All the LEDs placed in sequence represent a binary sequence or encoding of an analog value.

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542 Views

The emerging 5G services offer numerous new opportunities for networked applications. In this study, we seek to answer two key questions: i) is the throughput of mmWave 5G predictable, and ii) can we build "good" machine learning models for 5G throughput prediction? To this end, we conduct a measurement study of commercial mmWave 5G services in a major U.S. city, focusing on the throughput as perceived by applications running on user equipment (UE).

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1281 Views

India is known for its highly disciplined foreign policies, strategic location, vibrant and massive Diaspora. India envisages enhancing its scope of cooperation, trade and widens its sphere of relations with the Pacific. As a result, the world is witnessing the rise of Indo-Pacific ties. Before the 1980’s the keystone of the universe was called the Atlantic, but now a radical shift to the east is noticed by the term “Indo-Pacific‟.

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478 Views

YonseiStressImageDatabase is a database built for image-based stress recognition research. We designed an experimental scenario consisting of steps that cause or do not cause stress; Native Language Script Reading, Native Language Interview, Non-native Language Script Reading, Non-native Language Interview. And during the experiment, the subjects were photographed with Kinect v2. We cannot disclose the original image due to privacy issues, so we release feature maps obtained by passing through the network.

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2182 Views

The DREAM (Data Rang or EArth Monitoring): a multimode database including optics, radar, DEM and OSM labels for deep machine learning purposes.

DREAM, is a multimodal remote sensing database, developed from open-source data.

The database has been created using the Google Earth Engine platform, the GDAL python library; the “pyosm” python package developed by Alexandre Mayerowitz (Airbus, France). If you want to use this dataset in your study, please cite:

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690 Views

The data-set used in the paper titled "Short-Term Load Forecasting Using an LSTM Neural Network."

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1365 Views

Intracellular organelle networks such as the endoplasmic reticulum (ER) network and the mitochondrial network serve crucial physiological functions. Morphology of these networks plays critical roles in mediating their functions.Accurate image segmentation is required for analyzing morphology of these networks for applications such as disease diagnosis and drug discovery. Deep learning models have shown remarkable advantages in accurate and robust segmentation of these complex network structures.

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2358 Views

Basil/Tulsi Plant is harvested in India because of some spiritual facts behind this plant,this plant is used for essential oil and pharmaceutical purpose. There are two types of Basil plants cultivated in India as Krushna Tulsi/Black Tulsi and Ram Tulsi/Green Tulsi.

Many of the investigator working on disease detection in Basil leaves where the following diseases occur

 1) Gray Mold

2) Basal Root Rot, Damping Off

 3) Fusarium Wilt and Crown Rot

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5607 Views

This dataset contains 1216 data, which are scanned by HIS-RING PACT system.

the data sampling rate of our system is 40 MSa/s, a 128-elements 2.5MHz full-view ring-shaped transducer with 30mm radius. 

 continuous updating.....

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