Browsing Department of Computer Science and Engineering by Subject "Machine learning"
Now showing items 1-20 of 42
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ADAPTIVE HUMAN-ROBOT MOTION TRANSFER FOR COMPLETE BODY IMITATION
(2022-01-06)Programming robot systems to perform certain tasks is a big challenge especially if such programming is to be performed by persons who are not experts in robotics. For example, when programming a robot to serve as an ... -
ApproxML: Efficient Approximate Ad-Hoc ML Models Through Materialization and Reuse
(2019-12-10)Machine Learning (ML) has become an essential tool in answering complex predictive analytic queries. Model building for large scale datasets is one of the most time-consuming parts of the data science pipeline. Often data ... -
Classification of Factual and Non-Factual Statements Using Adversarially Trained LSTM Networks
(2020-06-08)Being able to determine which statements are factual and therefore likely candidates for further verification is a key value-add in any automated fact-checking system. For this task, it has been shown that LSTMs outperform ... -
COMPARISON OF MACHINE LEARNING ALGORITHMS IN SUGGESTING CANDIDATE EDGES TO CONSTRUCT A QUERY ON HETEROGENEOUS GRAPHS
(2016-05-11)Querying graph data can be difficult as it requires the user to have knowledge of the underlying schema and the query language. Visual query builders allow users to formulate the intended query by drawing nodes and edges ... -
Computer Vision Methods for Sign Language and Cognitive Evaluation through Physical Tasks
(2020-08-05)Analyzing human motion is vital for a multitude of tasks including human-computer interaction, sign language recognition, and the assessment of cognitive disorders. Providing automatic assessments for cognitive disorders ... -
Context-Aware Gaze-Based Interface for Smart Wheelchair
(2023-05-22)Human-Computer Interfaces (HCI) is an essential aspect of modern technology that has revolutionized the way we interact with machines. With the revolution of computers and smart devices and the advent of autonomous vehicles ... -
Convex and Non-convex Optimization Methods for Machine Learning
(2019-08-01)This dissertation is concerned with modeling fundamental and challenging machine learning tasks as convex/non-convex optimization problems and designing a mechanism that could solve them in a cost and time-effective manner. ... -
Deep Learning for Recognition of Objects, Activities, Faces, and Spatio-Temporal Patterns
A popular method in machine learning is Convolutional Neural Network (CNN). CNN had was of high interest to the research community in the 1990s, but after that its popularity receded compared to the Support Vector Machine ... -
Deep Reinforcement Learning-based Portfolio Management
(2019-05-16)Machine Learning is at the forefront of every field today. The subfields of Machine Learning called Reinforcement Learning and Deep Learning, when combined have given rise to advanced algorithms which have been successful ... -
Deep Representation Learning for Clustering and Domain Adaptation
(2019-12-05)Representation learning is a fundamental task in the area of machine learning which can significantly influence the performance of the algorithms used in various applications. The main goal of this task is to capture the ... -
DWRELU : DOUBLE WEIGHTED RECTIFIER LINEAR UNIT AN ACTIVATION FUNCTION WITH TRAINABLE SCALING PARAMETER
(2018-11-14)Deep Neural Network have become very popular for computer vision application in recent years. At the same time, it remains important to understand the different implementation choices that need to be made when designing a ... -
Efficient Construction and Explanation of Machine Learning Models through Database Techniques
(2020-08-19)Machine learning (ML) has been widely adopted in the last few years and it has had an undeniable impact on the ways many organizations make decisions. While great advances have been made in developing new ML algorithms and ... -
FACE DETECTION AND RECOGNITION USING MOVING WINDOW ACCUMULATOR WITH VARIOUS DEEP LEARNING ARCHITECTURE
(2018-05-04)Recent advancement in the field of Computer Vision and Deep Learning is making object detection and recognition easier. Hence, growing research activities in the field of deep learning are enabling researchers to find new ... -
Feature Extraction In Noise-Diverse Environments For Human Activities Recognition Using Wi-Fi
(2019-12-04)With the rapid development of 802.11 standard and Internet of Things (IoT) applications, Wi-Fi (IEEE 802.11) has emerged as the most widely used wireless communication technology. Wi-Fi based sensing has found widespread ... -
FROM BODY TO BRAIN: USING ARTIFICIAL INTELLIGENCE TO IDENTIFY USER SKILLS & INTENTIONS IN INTERACTIVE SCENARIOS
(2019-04-23)Artificial Intelligence has probably been the most rapidly evolving field of science during the last decade. Its numerous real-life applications have radically altered the way we experience daily-living with great impact ... -
FROM TEXT CLASSIFICATION TO IMAGE CLUSTERING, PROBLEMS LESS OPTIMIZED
(2018-06-11)Machine Learning is thriving. Every industry is using its techniques in some way to improve their efficiency and revenue. However, the focus on research is not divided equally between all of the different areas and problems ... -
GENERATING ADVERSARIAL EXAMPLES FOR RECRUITMENT RANKING ALGORITHMS
(2020-12-16)There is no doubt that recruitment process plays an important role for both employers and applicants. Based on huge number of job candidates and open vacancies, recruitment process is expensive, time consuming and stressful ... -
Hand-Over-Face Segmentation
(2020-08-04)Accurate hand segmentation is vital in many applications in which the hands play a central role, such as sign language recognition, action recognition, and gesture recognition. A relatively unexplored obstacle to correct ... -
HEALTH MONITORING OF ATLAS DATA CENTER CLUSTERS AND FAILURE ANALYSIS
(2018-12-06)Monitoring the health of data center clusters is an integral part of any industrial facility. ATLAS is one of the High Energy Physics experiments at the Large Hadron Collider (LHC) at CERN. ATLAS DDM (Distributed Data ... -
HUMAN FACTORS ANALYSIS AND MONITORING TO ENHANCE HUMAN-ROBOT COLLABORATION
(2021-05-11)Human-Machine Interaction (HMI) can be defined as a way for us to communicate with machines through user interfaces. User interfaces have evolved from complicated punch cards and levers in the first analog computers to a ...