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Full-Text Articles in Engineering
Quantification Of Energy Intake Using Food Image Analysis, Sertan Kaya
Quantification Of Energy Intake Using Food Image Analysis, Sertan Kaya
LSU Master's Theses
Obtaining real-time and accurate estimates of energy intake while people reside in their natural environment is technically and methodologically challenging. The goal of this project is to estimate energy intake accurately in real-time and free-living conditions. In this study, we propose a computer vision based system to estimate energy intake based on food pictures taken and emailed by subjects participating in the experiment. The system introduces a reference card inclusion procedure, which is used for geometric and photometric corrections. Image classification and segmentation methods are also incorporated into the system to have fully-automated decision making.
A Probabilistic Approach For Modeling And Real-Time Filtering Of Freeway Detector Data, Shourie Kondagari
A Probabilistic Approach For Modeling And Real-Time Filtering Of Freeway Detector Data, Shourie Kondagari
LSU Master's Theses
Traffic surveillance systems are a key component for providing information on traffic conditions and supporting traffic management functions. A large amount of data is currently collected from inductive loop detector systems in the form of three macroscopic traffic parameters (speed, volume and occupancy). Such information is vital to the successful implementation of transportation data warehouses and decision support systems. The quality of data is, however, affected by erroneous observations that result from malfunctioning or mis-calibration of detectors. The open literature shows that little effort has been made to establish procedures for screening traffic observations in real-time. This study presents a …
Image Processing Techniques To Identify Predatory Birds In Aquacultural Settings, Uma Devi Nadimpalli
Image Processing Techniques To Identify Predatory Birds In Aquacultural Settings, Uma Devi Nadimpalli
LSU Master's Theses
Bird predation is a major problem in aquaculture. A novel method for dispersing birds is the use of a vehicle that can sense and chase birds. Image recognition software can improve their efficiency in chasing birds. Three recognition techniques were tested to identify birds 1) image morphology 2) artificial neural networks, and 3) template matching have been tested. A study was conducted on three species of birds 1) pelicans, 2) egrets, and 3) cormorants. Images were divided into 3 types 1) Type 1, 2) Type 2, and 3) Type 3 depending upon difficulty to separate from the others in the …
Computer-Aided Diagnosis Tool For The Detection Of Cancerous Nodules In X-Ray Images, Pallavi Bomma
Computer-Aided Diagnosis Tool For The Detection Of Cancerous Nodules In X-Ray Images, Pallavi Bomma
LSU Master's Theses
This thesis involves development of a computer-aided diagnosis (CAD) tool for the detection of cancerous nodules in X-ray images. Both cancerous and non-cancerous regions appear with little distinction on an X-ray image. For accurate detection of cancerous nodules, we need to differentiate the cancerous nodules from the non-cancerous. We developed an artificial neural network to differentiate them. Artificial neural networks (ANN) find a large application in the area of medical imaging. They work in a manner rather similar to the brain and have good decision making criteria when trained appropriately. We trained the neural network by the backpropagation algorithm and …
A Hybrid Model-Based And Memory-Based Short-Term Traffic Prediction System, Ciprian Danut Alecsandru
A Hybrid Model-Based And Memory-Based Short-Term Traffic Prediction System, Ciprian Danut Alecsandru
LSU Master's Theses
Short-term traffic forecasting capabilities on freeways and major arterials have received special attention in the past decade due primarily to their vital role in supporting various travelers' trip decisions and traffic management functions. This research presents a hybrid model-based and memory-based methodology to improve freeway traffic prediction performance. The proposed methodology integrates both approaches to strengthen predictions under both recurrent and non-recurrent conditions. The model-based approach relies on a combination of static and dynamic neural network architectures to achieve optimal prediction performance under various input and traffic condition settings. Concurrently, the memory-based component is derived from the data archival system …