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Full-Text Articles in Computer Engineering
Localization Using Convolutional Neural Networks, Shannon D. Fong
Localization Using Convolutional Neural Networks, Shannon D. Fong
Computer Engineering
With the increased accessibility to powerful GPUs, ability to develop machine learning algorithms has increased significantly. Coupled with open source deep learning frameworks, average users are now able to experiment with convolutional neural networks (CNNs) to solve novel problems. This project sought to train a CNN capable of classifying between various locations within a building. A single continuous video was taken while standing at each desired location so that every class in the neural network was represented by a single video. Each location was given a number to be used for classification and the video was subsequently titled locX. These …
Lionfish Detection System, Carmelo Furlan, Andrew Boniface
Lionfish Detection System, Carmelo Furlan, Andrew Boniface
Computer Engineering
Deep neural networks have proven to be an effective method in classification of images. The ability to recognize objects has opened the door for many new systems which use image classification to solve challenging problems where conventional image classification would be inadequate. We trained a large, deep convolutional neural network to identify lionfish from other species that might be found in the same habitats. Google’s Inception framework served as a powerful platform for our fish recognition system. By using transfer learning, we were able to obtain exceptional results for the classification of different species of fish. The convolutional neural network …
Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto
Underwater Computer Vision - Fish Recognition, Spencer Chang, Austin Otto
Computer Engineering
The Underwater Computer Vision – Fish Recognition project includes the design and implementation of a device that can withstand staying underwater for a duration of time, take pictures of underwater creatures, such as fish, and be able to identify certain fish. The system is meant to be cheap to create, yet still able to process the images it takes and identify the objects in the pictures with some accuracy. The device can output its results to another device or an end user.
Multispectral Identification Array, Zachary D. Eagan
Multispectral Identification Array, Zachary D. Eagan
Computer Engineering
The Multispectral Identification Array is a device for taking full image spectroscopy data via the illumination of a subject with sixty-four unique spectra. The array combines images under the illumination spectra to produce an approximate reflectance graph for every pixel in a scene. Acquisition of an entire spectrum allows the array to differentiate objects based on surface material. Spectral graphs produced are highly approximate and should not be used to determine material properties, however the output is sufficiently consistent to allow differentiation and identification of previously sampled subjects. While not sufficiently advanced for use as a replacement to spectroscopy the …
California Polytechnic State University Senior Project Winter-Spring 2012, Roborodentia Xvii, Stack-E, Alejandro Ignacio, Austin Hobbs
California Polytechnic State University Senior Project Winter-Spring 2012, Roborodentia Xvii, Stack-E, Alejandro Ignacio, Austin Hobbs
Computer Engineering
The main goal for our project is to design and build a functional autonomous robot that is capable of navigating an open arena while avoiding obstacles, as well as identify other objects or cans on the field. It must also be capable of stacking and containing these cans. Deliverables will include the fully assembled robot chassis containing the essential hardware components needed to accomplish the navigation and movement, as well as capabilities like identification of objects and stacking of cans. Alongside the hardware, there will also be software developed to showcase these capabilities of the robot design, including the vision …
Markerless Affine Region Tracking And Augmentation Using Mser And Sift, Gregory (Greg) Eddington Ii
Markerless Affine Region Tracking And Augmentation Using Mser And Sift, Gregory (Greg) Eddington Ii
Computer Engineering
Due to the advancements in mobile computing hardware and the inclusion of cameras in many computing platforms, augmented reality systems have become widely available. This paper presents a real-time implementation of a novel markerless augmented reality algorithm which is able to track two-dimensional affine regions without a priori information of the environment or computing a world model. The implementation consists of the MAR library; a modular software library which performs the region detection, identification, and tracking; and the Lighthouse application; a program which uses the MAR library to allow the user to augment scenes viewed from a camera. The algorithm …