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Second chance competitive autoencoders for understanding textual data
(2021)
Every day, an enormous amount of text data is produced. Sources of text data include news, social media, emails, text messages, medical reports, scientific publications, and fiction. To keep track of this data, there are ...
Design of Multi-modality Deep Fusion Architecture for Deep Acoustic Analytics
(2021)
There is increasing attention for audio classification research to support various emerging applications, including environmental monitoring, health care, and smart city. Audio classification is an important area of research ...
AI-based Edge Computing System for Event Based Analytics
(2021)
In recent years, the Internet of Things (IoT) has received lots of attention due to its promising applications. Along with IoT evolution, we have witnessed advanced research for edge computing and its potential benefits ...
On-chip Voltage Regulator– Circuit Design and Automation
(2021)
With the increase of density and complexity of high-performance integrated circuits and systems, including many-core chips and system-on-chip (SoC), it is becoming difficult to meet the power delivery and regulation ...
Modeling and simulation of silicon photonics based optical ring resonator biosensor
(2021)
In the photonic technological platforms, the signal is carried by light rather than an electron as in conventional electronic technologies. Electronic processing of the signals is becoming restricted, particularly in the ...
GraphEvo: Evaluating Software Evolution Using Machine Learning Based Call Graph Analytics And Network Portrait Divergence
(2022)
Understanding software evolution is essential for software development tasks, including debugging, maintenance, and testing. Unfortunately, as software changes, it becomes more prominent and more complicated, which makes ...
Software Analytics for Improving Program Comprehension
(2021)
Program comprehension is an essential part of software development and maintenance. Traditional methods of program comprehension, such as reviewing the codebase and documentation, are still challenging for understanding ...
Decision Support System for Pull Requests Review Using Path-based Network Portrait Divergence and Visualization
(2022)
Pull requests are widely used in open-source and
industrial environments to contribute and assess contributions.
Unlike the typical code review process, pull requests provide
a more lightweight approach for committing, ...
P2P Based Personalized Federated Learning for Collaborative Model Sharing and Inferencing
(2022)
Existing Federated Learning (FL) relies primarily on client-server architecture to train a single global model utilizing various local datasets. There are ongoing initiatives to improve the present state of federated ...
Deep Open Representative Learning for Image and Text Classification
(2020)
An essential goal of artificial intelligence is to support the knowledge discovery process from data to the knowledge that is useful in decision making. The challenges in the knowledge discovery process are typically due ...
Class Representative Projection for Text-based Zero-Shot Learning
(2020)
There have been significant advances in supervised machine learning and enormous benefits from deep learning for a range of diverse applications. Despite the success of deep learning, in reality, very few works have shown ...
Multi-Modal Topic Sentiment Analytics for Twitter
(University of Missouri -- Kansas City, 2018)
Sentiment analysis has proven to be very successful in text applications. Social media
is also considered a quite rich source to get data regarding user’s behaviors and
preference. Identifying social context would make ...
MDRED: Multi-Modal Multi-Task Distributed Recognition for Event Detection
(University of Missouri -- Kansas City, 2018)
Understanding users’ context is essential in emerging mobile sensing applications, such
as Metal Detector, Glint Finder, Facefirst. Over the last decade, Machine Learning (ML)
techniques have evolved dramatically for ...
3D Hand Pose Estimation Via a Lightweight Deep Learning Model
(University of Missouri -- Kansas City, 2018)
Deep Learning with depth cameras has enabled 3D hand pose estimation from RGBD
images. Commercial solutions like Leap Motion and Intel RealSense™ use stereoscopic sensors or
IR illumination-based methods to capture the ...
SAF-DL: Semantic Analysis Framework for Deep Learning Open Source Projects
(University of Missouri--Kansas City, 2018)
There are a lot of open source projects available on the internet. Specifically, due to the
increasing interest of Deep Learning (DL), the number of DL open source projects is also
increased. This project is motivated ...
Identifying personality and topics of social media
(2019)
Twitter and Facebook are the renowned social networking platforms where users post, share, interact and express to the world, their interests, personality, and behavioral information. User-created content on social media ...
Multi-modal emotion detection using deep learning for interpersonal communication analytics
(2019)
In recent years, deep learning technologies have been increasingly applied to generate meaningful data for advanced research in humanities and sciences. Interpersonal communication skills are crucial to success in science. ...
Context Based Multi-Image Visual Question Answering (VQA) in Deep Learning
(University of Missouri--Kansas City, 2017)
Image question answering has gained huge popularity in recent years due to
advancements in Deep Learning technologies and computer processing hardware which are
able to achieve higher accuracies with faster processing ...
H3DNET: A Deep Learning Framework for Hierarchical 3D Object Classification
(University of Missouri--Kansas City, 2017)
Deep learning has received a lot of attention in the fields such as speech recognition and
image classification because of the ability to learn multiple levels of features from raw data.
However, 3D deep learning is ...
Deep Assertion discovery using word embeddings
(University of Missouri -- Kansas City, 2018)
In recent years, there has been explosive growth in the amount of biomedical data
(e.g., publications, notes from EHRs, clinical trial results), with the majority being
unstructured data. As the volume of data is ...