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Full-Text Articles in Physical Sciences and Mathematics
Image-Based Cancer Diagnosis Using Novel Deep Neural Networks, Hosein Barzekar
Image-Based Cancer Diagnosis Using Novel Deep Neural Networks, Hosein Barzekar
Theses and Dissertations
Cancer is the major cause of death in many nations. This serious illness can only be effectivelytreated if it is diagnosed early. In contrast, biomedical imaging presents challenges to both clinical institutions and researchers. Physiological anomalies are often characterized by modest modifications in individual cells or tissues, making them difficult to detect visually. Physiological anomalies are often characterized by slight abnormalities in individual cells or tissues, making them difficult to detect visually. Traditionally, anomalies are diagnosed by radiologists and pathologists with extensive training. This procedure, however, demands the participation of professionals and incurs a substantial expense, making the classification of …
Novel Deep Neural Network For Medical Image Classification, Dm Anisuzzaman
Novel Deep Neural Network For Medical Image Classification, Dm Anisuzzaman
Theses and Dissertations
Medical image classification is an essential part of diagnosis, which with automation may benefit both physicians and patients in terms of time and cost. For automation, different Artificial intelligence (AI) methods, including Machine Learning (ML) and Deep Learning (DL), are used widely. Specifically, DL algorithms have become popular in classifying medical images due to their propensity for good performance. This thesis studies medical image classification problems using deep learning models. Four specific medical applications are considered: (1) Osteosarcoma cancer classification in histological images, (2) Burn wound classification, (3) Wound severity classification from clinical images, and (4) Wound type classification using …
An Empirical Study On Sampling Approaches For 3d Image Classification Using Deep Learning, Nicholas Michelette
An Empirical Study On Sampling Approaches For 3d Image Classification Using Deep Learning, Nicholas Michelette
Theses and Dissertations
A 3D classification method requires more training data than a 2D image classification method to achieve good performance. These training data usually come in the form of multiple 2D images (e.g., slices in a CT scan) or point clouds (e.g., 3D CAD modeling) for volumetric object representation. The amount of data required to complete this higher dimension problem comes with the cost of requiring more processing time and space. This problem can be mitigated with data size reduction (i.e., sampling). In this thesis, we empirically study and compare the classification performance and deep learning training time of PointNet utilizing uniform …
Terrestrial Perspective On The Formation, Evolution, And Detection Of Zeolites In Lacustrine Environments On Early Mars, Gayantha Roshana Loku Kodikara
Terrestrial Perspective On The Formation, Evolution, And Detection Of Zeolites In Lacustrine Environments On Early Mars, Gayantha Roshana Loku Kodikara
Theses and Dissertations
This study evaluates the possible formation and evolution mechanisms of zeolites on early Mars with possible explanations for their limited detections using Earth analogs. This study focuses on the formation of zeolites in the closed basin lakes where the largest relatively pure concentrations of natural zeolites are found on Earth. Five working hypotheses were formulated to explore the limited detection of zeolites in closed basin lakes on Mars and different styles of scientific reasoning with suitable examples were used to test the independent, converging lines of inquiry. Zeolites may not be identifiable in certain locations on Mars using orbital data …
Deep Learning Based Generative Materials Design, Yong Zhao
Deep Learning Based Generative Materials Design, Yong Zhao
Theses and Dissertations
Discovery of novel functional materials is playing an increasingly important role in many key industries such as lithium batteries for electric vehicles and cell phones. However experimental tinkering of existing materials or Density Functional Theory (DFT) based screening of known crystal structures, two of the major current materials design approaches, are both severely constrained by the limited scale (around 250,000 in ICSD database) and diversity of existing materials and the lack of a sufficient number of materials with annotated properties. How to generate a large number of physically feasible, stable, and synthesizable crystal materials and build accurate property prediction models …
Smart City Management Using Machine Learning Techniques, Mostafa Zaman
Smart City Management Using Machine Learning Techniques, Mostafa Zaman
Theses and Dissertations
In response to the growing urban population, "smart cities" are designed to improve people's quality of life by implementing cutting-edge technologies. The concept of a "smart city" refers to an effort to enhance a city's residents' economic and environmental well-being via implementing a centralized management system. With the use of sensors and actuators, smart cities can collect massive amounts of data, which can improve people's quality of life and design cities' services. Although smart cities contain vast amounts of data, only a percentage is used due to the noise and variety of the data sources. Information and communication technology (ICT) …