Index Catalog // ScholarsArchive@OSU

Image features and learning algorithms for biological, generic and social object recognition

Creator:: Zhang, Wei
Abstract:: Automated recognition of object categories in images is a critical step for many real-world computer vision applications. Interest region detectors and region descriptors have been widely employed to tackle the variability of objects in pose, scale, lighting, texture, color, and so on. Different types of object recognition problems usually require...
Resource Type:: Dissertation
Full Text:: Fern, Professor Prasad Tadepalli, Professor Xiaoli Fern, and Professor Yun-Shik Lee. Their kindly

Information-theoretic Approach to Design and Evaluate Privacy-preserving and Fair Frameworks for Continuous High-dimensional Data

Creator:: Alsulaimawi, Zahir Ahmed Hussein
Abstract:: Deep learning is becoming the latest trend in sensitive applications, such as healthcare, criminal justice, and finance. As these new applications emerge, adversaries are circumventing them. Further, there have been concerns about the possibility of bias and discrimination in predictive applications. In order to address these issues, we propose an...
Resource Type:: Dissertation

Exploration of regression models for cancer noncoding mutation recurrence

Creator:: Xu, Tanjin
Abstract:: An important impact of the genome technology revolution will be the elucidation of mechanisms of cancer pathogenesis, leading to improvements in the diagnosis of cancer and the selection of cancer treatment. Integrated with current well-studied massive knowledge and findings about the role of protein-coding mutations in cancer, demystifying the functional...
Resource Type:: Masters Thesis

A study of methods for fine-grained object classification of arthropod specimens

Creator:: Lin, Junyuan
Abstract:: Object categorization is one of the fundamental topics in computer vision research. Most current work in object categorization aims to discriminate among generic object classes with gross differences. However, many applications require much finer distinctions. This thesis focuses on the design, evaluation and analysis of learning algorithms for fine- grained...
Resource Type:: Masters Thesis

Coupled Compressive Sensing : Sequential Reinforcement Approach

Creator:: De Silva, Shashini A.
Abstract:: We consider multiple Compressive Sensing (CS) problems wherein the supports of signal vectors of CS problems are restricted to satisfy a collection of joint logical constraints, which we refer to as coupling constraints. We consider a case where the coupling constraints are encoded in a graph and present a sequential...
Resource Type:: Masters Thesis
Full Text:: Transactions on Power Systems, 27(4):2215–2224, 2012. [9] Lee C Potter, Emre Ertin, Jason T Parker, and

Data Classification and Extraction of Weather Reports

Creator:: Qin, Rui
Abstract:: Severe weather in the United States causes huge insured losses to crop and property frequently.It creates major impact and elicit diverse response in the weather insurance industry. Events like hail, storm, hurricane etc. are more likely to cause catastrophe losses. So it becomes crucial to collect and analyze these extreme...
Resource Type:: Capstone Project

Rare category detection using hierarchical mean shift

Creator:: Vatturi, Pavan Kumar
Abstract:: Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to identify statistically significant anomalies, a more difficult task is to identify anomalies that are both interesting and statistically significant. Category detection is an emerging area of machine learning...
Resource Type:: Masters Thesis

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

Creator:: Aziere, Nicolas
Abstract:: This paper addresses the high model complexity and overconfident frame labeling of state-of-the-art (SOTA) action segmenters. Their complexity is typically justified by the need to sequentially refine action segmentation through multiple stages of a deep architecture. However, this multistage refinement does not take into account uncertainty of frame labeling predicted...
Resource Type:: Dissertation

Secure Data Analytics under Data Integrity Attacks

Creator:: De Silva, Shashini A.
Abstract:: There has been tremendous growth in using data analytic and machine learning algorithms to make critical decisions, such as in the national power grid, healthcare operations, and autonomous vehicles. Employing data analytic for decision-making allows cyber attackers to manipulate the decisions of these algorithms through data falsification. Hence, the trustworthiness...
Resource Type:: Dissertation

Interpretable Machine Learning: Applications in Biology and Genomics

Creator:: Danaee, Padideh
Abstract:: Machine learning (ML) and deep learning (DL) models impact our daily lives with applications in natural language modeling, image analysis, healthcare, genomics, and bioinformatics. The exponential growth of biological sequence data necessitates accompanying advances in computational methods. Although deep learning is highly effective for detecting and classifying biological sequences, challenges...
Resource Type:: Dissertation

ScholarsArchive@OSU

Image features and learning algorithms for biological, generic and social object recognition

Information-theoretic Approach to Design and Evaluate Privacy-preserving and Fair Frameworks for Continuous High-dimensional Data

Exploration of regression models for cancer noncoding mutation recurrence

A study of methods for fine-grained object classification of arthropod specimens

Coupled Compressive Sensing : Sequential Reinforcement Approach

Data Classification and Extraction of Weather Reports

Rare category detection using hierarchical mean shift

Action Segmentation in Videos: Deep Models, Prediction Diffusion, and Deep-Temporal Augmentations

Secure Data Analytics under Data Integrity Attacks

Interpretable Machine Learning: Applications in Biology and Genomics

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