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Found 10 papers, 3 papers with code
DAAI at CASE 2021 Task 1: Transformer-based Multilingual Socio-political and Crisis Event Detection
Automatic socio-political and crisis event detection has been a challenge for natural language processing as well as social and political science communities, due to the diversity and nuance in such events and high accuracy requirements.
MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification
It exploits the high sensitivity to the multi-level contextual information using an uncertainty quantification component to accomplish a novel dynamic ensemble model. MCUamodelhas achieved a high accuracy of 98. 11% on a breast cancer histology image dataset.
Breast Cancer Histology Image Classification
Classification
+1
Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media
Social media is becoming a primary medium to discuss what is happening around the world.
Co-eye: A Multi-resolution Symbolic Representation to TimeSeries Diversified Ensemble Classification
The developed technique similarly uses different lenses and representations to look at the time series, and then combines them for broader visibility.
DeepStreamCE: A Streaming Approach to Concept Evolution Detection in Deep Neural Networks
For comparison, we apply the data and VGG16 networks to an open-set deep network solution - OpenMax.
Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network
Due to the high availability of large-scale annotated image datasets, great success has been achieved using convolutional neural networks (CNNs) for image recognition and classification.
A Heuristically Modified FP-Tree for Ontology Learning with Applications in Education
Subject experts rated the quality of the system's answers on a subset of questions and their ratings were used to identify the most appropriate automatic semantic text similarity metric to use as a validation metric for all answers.
EnSyth: A Pruning Approach to Synthesis of Deep Learning Ensembles
In this paper, we describe EnSyth, a deep learning ensemble approach to enhance the predictability of compact neural network's models.
AnyThreat: An Opportunistic Knowledge Discovery Approach to Insider Threat Detection
To address this shortcoming, we propose an opportunistic knowledge discovery system, namely AnyThreat, with the aim to detect any anomalous behaviour in all malicious insider threats.
A Survey of Data Mining Techniques for Social Media Analysis
Data mining techniques are used for information retrieval, statistical modelling and machine learning.
