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EXPERIMENTS IN TEXT SUMMARIZATION USING DEEP LEARNING
Title
EXPERIMENTS IN TEXT SUMMARIZATION USING DEEP LEARNING
Author
Bulusu, Sai Amrit
Date Created
2018
Subjects--Topical
Computer science, Artificial intelligence, Information science
Description
Deep Learning has been the go-to tool for text summarization in the recent times.Traditional deep learning research focuses on performing abstractive text summarizationwithout considering the user’s interests to personalize the summaries.This prob...
Prediction of Cis-regulatory Modules in Genomes
Title
Prediction of Cis-regulatory Modules in Genomes
Author
Ni, Pengyu
Date Created
2020
Subjects--Topical
Bioinformatics
Description
Annotating all cis-regulatory modules (CRMs) and constituent transcription factor (TF) binding sites (TFBSs) in genomes is essential to understand genome functions, however, the task remains highly challenging. In this dissertation, we first devel...
Autonomous Cyber Defense: Formal Models and Applications
Title
Autonomous Cyber Defense: Formal Models and Applications
Author
Dutta, Ashutosh
Date Created
2021
Subjects--Topical
Computer science, Information science, Information technology
Description
With technological advancements, cyber attacks are highly automated and organized with asymmetric advantages over defenders regarding cost and efforts.Attackers employ sophisticated and diversified approaches to achieve attack objectives while bei...
Faster Convolutional Neural Networks Training
Title
Faster Convolutional Neural Networks Training
Author
Jiang, Shanshan
Date Created
2021
Subjects--Topical
Computer science
Description
Convolutional Neural Network (CNN) models have become the mainstream method in Artificial Intelligence (AI) areas for computer vision tasks like image classification and image segmentation. Deep CNNs contain a large volume of convolution calculati...
MODELING UNCERTAINTY IN DEEP LEARNING MODELS OF ELECTRONIC HEALTH RECORDS
Title
MODELING UNCERTAINTY IN DEEP LEARNING MODELS OF ELECTRONIC HEALTH RECORDS
Author
Qiu, Riyi
Date Created
2020
Subjects--Topical
Information technology
Description
Recent research development has demonstrated the advantages of deep learning models in prediction tasks on electronic health records (EHR) in the medical domain. However, the prediction results tend to be difficult to explain due to the complex ne...
Detecting Discrete Emotions in Text Using Neural Networks
Title
Detecting Discrete Emotions in Text Using Neural Networks
Author
Seyeditabari, Seyed Armin
Date Created
2020
Subjects--Topical
Computer science, Artificial intelligence
Description
In recent years, emotion detection in text has become increasingly popular because of its many potential applications in a range of areas, such as marketing, political science, psychology, human-computer interaction, artificial intelligence. Acces...
Deep Learning for Sentiment and Emotion Detection in Multilingual Contexts
Title
Deep Learning for Sentiment and Emotion Detection in Multilingual Contexts
Author
Abdullah, Malak
Date Created
2018
Subjects--Topical
Computer science
Description
Social media is growing as a communication medium where people can express online their feelings and opinions on a variety of topics in ways they rarely do in person. Detecting sentiments and emotions in texts have gained a considerable amount of ...
Deep Neural Language Generation with Emotional Intelligence and External Feedback
Title
Deep Neural Language Generation with Emotional Intelligence and External Feedback
Author
Srinivasan, Vidhushini
Date Created
2018
Subjects--Topical
Computer science
Description
Neural seq2seq models are widely used to generate dialogue using variations of RNN Encoder-Decoder architecture with maximum likelihood estimation as objective function. Advances in this architecture include introducing reinforcement learning to t...
Emergency Medical Services Demand Forecasting: Modern Machine Learning Approaches For Producing Short-Term Spatiotemporal Estimations
Title
Emergency Medical Services Demand Forecasting: Modern Machine Learning Approaches For Producing Short-Term Spatiotemporal Estimations
Author
Martin, Richard
Date Created
2019
Subjects--Topical
Operations research, Information technology
Description
Emergency medical services (EMS); commonly referred to as ambulance, paramedic or pre-hospital emergency services, are a critical component in the delivery of urgent medical care to communities. EMS agencies, the organizations responsible for prov...
Fracture properties of graphene-like two-dimensional materials and topology optimization through neural networks for coupled thermo-mechanical problems
Title
Fracture properties of graphene-like two-dimensional materials and topology optimization through neural networks for coupled thermo-mechanical problems
Author
Shishir, Md Imrul Reza
Date Created
2022
Subjects--Topical
Mechanical engineering, Mechanics, Materials science
Description
Part I: Study of fracture properties of graphene--like two--dimensional materials using molecular dynamics (MD) simulationsGraphene is a monoatomic thick sheet of sp2-hybridized carbon atoms tightly packed in a honeycomb lattice structure. It has ...
Ultra Low Power Techniques for Machine Learning on the Edge
Title
Ultra Low Power Techniques for Machine Learning on the Edge
Author
Hasan, Md Munir
Date Created
2022
Subjects--Topical
Electrical engineering, Neurosciences
Description
Deep learning has become an integral part of machine learning. It has radically transformed our lives in healthcare, automotive systems, human computer interaction etc. Although, deep learning requires a tremendous amount of compute power and reso...
A Scalable deep learning framework for autonomous road asset classification
Title
A Scalable deep learning framework for autonomous road asset classification
Author
Nouri Gooshki, Sadegh
Date Created
2019
Subjects--Topical
Artificial intelligence
Description
The focus of this thesis is on automation in road asset inspection using deep neural networks. Even though some progress has been made in automation of data collection and condition assessment, the amount of manual operation and the cost of road i...
'Practice' for Enhancing the Performance of a Deep Reinforcement Learning Agent
Title
'Practice' for Enhancing the Performance of a Deep Reinforcement Learning Agent
Author
Kancharla, Venkata Sai Santosh Ravi Teja
Date Created
2019
Subjects--Topical
Artificial intelligence
Description
Deep reinforcement learning has demonstrated its capability to solve a diverse array of challenging problems, which were not able to solve previously. It has been able to achieve human-level performance in Atari 2600 games and it has shown great p...
Comparison between statistical and deep learning approaches for anomaly detection applications in a microgrid
Title
Comparison between statistical and deep learning approaches for anomaly detection applications in a microgrid
Author
Bhure, Chaitanya
Date Created
2020
Subjects--Topical
Electrical engineering
Description
A microgrid is a localized group of electricity sources and loads that normally operates connected to and synchronous with traditional wide area synchronous grid(macrogrid), but can also disconnect to island mode and then function autonomouslyas p...
Algorithmic Optimization of First Convolution Layer in CNNs for Hardware Accelerator Design
Title
Algorithmic Optimization of First Convolution Layer in CNNs for Hardware Accelerator Design
Author
Chamarthi, Ramachandra Vikas
Date Created
2019
Subjects--Topical
Electrical engineering, Computer engineering
Description
This thesis proposes "1D Convolution replacement layer ", a novel optimization for first convolution layer in CNN. This optimization enables edge friendly streaming accelerator design with a minimum drop in accuracy. This optimization reduces the ...
Object detection in aerial image
Title
Object detection in aerial image
Author
Li, Changlin
Date Created
2020
Subjects--Topical
Computer science
Description
Object detection in high-resolution aerial images is a challenging task because of1) the large variation in object size, and 2) non-uniform distribution of objects. A common solution is to divide the large aerial image into small (uniform) crops a...
PREPARATION OF UNITED STATES’ STATE COURT CASES DATASET AND DERIVING AN EFFICIENT EMBEDDING FOR CASES
Title
PREPARATION OF UNITED STATES’ STATE COURT CASES DATASET AND DERIVING AN EFFICIENT EMBEDDING FOR CASES
Author
Ravi, Karthik
Date Created
2019
Subjects--Topical
Computer science, Political science
Description
Data mining techniques gained acceptance as a clear means of finding information in data. In the past, these techniques have been effectively applied to discover patterns, find correlations, extract information from unstructured data. Often overlo...
Urban Dynamics: Longitudinal Causal Relationships And Future Time Series Forecasting
Title
Urban Dynamics: Longitudinal Causal Relationships And Future Time Series Forecasting
Author
Hatami, Faizeh
Date Created
2023
Subjects--Topical
City planning
Description
Studying urban dynamics is essential given the ever-increasing changes in urban areas with all its ensuing consequences, whether negative or positive. It is of paramount importance to take into account the temporal dimension of urban dynamics when...
Data Mining and Deep Learning Systems for Network Traffic Classification and Characterization at Scale
Title
Data Mining and Deep Learning Systems for Network Traffic Classification and Characterization at Scale
Author
Kapoor, Maya
Date Created
2023
Subjects--Topical
Computer science
Description
The real, complex network environment consists of an ever-increasingly diverse and large amount of data encapsulated in packets. Surveillance and monitoring of this traffic is a necessary task for law enforcement, cybersecurity, and intelligence a...
Interactive Mining for Large-scale Neuro-Morphological Datasets
Title
Interactive Mining for Large-scale Neuro-Morphological Datasets
Author
Li, Zhongyu
Date Created
2018
Subjects--Topical
Computer science, Neurosciences, Biomedical engineering
Description
In this dissertation, we aim to investigate advanced methods for the computational analytics of large-scale neuro-morphological datasets, which can help neuroscientists interactively explore neurons in real-time. Particularly, we tackle the neuro-...