Search Results for author:
Found 11 papers, 5 papers with code
Learning Cross-Task Attribute - Attribute Similarity for Multi-task Attribute-Value Extraction
We perform detailed experiments to show that our method indeed increases the macro-F1 scores for attribute value extraction in general, and for labels with low training data in particular.
Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Images
Magnetic Resonance Imaging (MRI) is the most commonly used non-intrusive technique for medical image acquisition.
On the Relationship Between Ground- and Satellite- Based Global Horizontal Irradiance
Global horizontal irradiance (GHI) plays a significant role in maintaining the earth's ecological balance and generating electricity in photovoltaic systems.
Monitoring Atmospheric Pollutants From Ground-based Observations
Remote sensing analysts continuously monitor the amount of pollutants in the atmosphere.
Detecting Blurred Ground-based Sky/Cloud Images
To the best of our knowledge, our approach is the first of its kind in the automatic identification of blurred images for ground-based sky/cloud images.
Using GANs to Augment Data for Cloud Image Segmentation Task
While cloud/sky image segmentation has extensive real-world applications, a large amount of labelled data is needed to train a highly accurate models to perform the task.
A Clustering Framework for Residential Electric Demand Profiles
The availability of residential electric demand profiles data, enabled by the large-scale deployment of smart metering infrastructure, has made it possible to perform more accurate analysis of electricity consumption patterns.
Validating Clustering Frameworks for Electric Load Demand Profiles
Clustering analysis of these profiles is important to further analyze and comment on electricity consumption patterns.
Forecasting Precipitable Water Vapor Using LSTMs
Long-Short-Term-Memory (LSTM) networks have been used extensively for time series forecasting in recent years due to their ability of learning patterns over different periods of time.
Language Identification and Morphosyntactic Tagging: The Second VarDial Evaluation Campaign
We present the results and the findings of the Second VarDial Evaluation Campaign on Natural Language Processing (NLP) for Similar Languages, Varieties and Dialects.
Automatic Identification of Closely-related Indian Languages: Resources and Experiments
In this paper, we discuss an attempt to develop an automatic language identification system for 5 closely-related Indo-Aryan languages of India, Awadhi, Bhojpuri, Braj, Hindi and Magahi.
