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Full-Text Articles in Physical Sciences and Mathematics
An Application Of Deep Learning Models To Automate Food Waste Classification, Alejandro Zachary Espinoza
An Application Of Deep Learning Models To Automate Food Waste Classification, Alejandro Zachary Espinoza
Dissertations and Theses
Food wastage is a problem that affects all demographics and regions of the world. Each year, approximately one-third of food produced for human consumption is thrown away. In an effort to track and reduce food waste in the commercial sector, some companies utilize third party devices which collect data to analyze individual contributions to the global problem. These devices track the type of food wasted (such as vegetables, fruit, boneless chicken, pasta) along with the weight. Some devices also allow the user to leave the food in a kitchen container while it is weighed, so the container weight must also …
Detecting Digitally Forged Faces In Online Videos, Neilesh Sambhu
Detecting Digitally Forged Faces In Online Videos, Neilesh Sambhu
USF Tampa Graduate Theses and Dissertations
We use Rossler’s FaceForensics dataset of 1004 online videos and their corresponding forged counterparts [1] to investigate the ability to distinguish digitally forged facial images from original images automatically with deep learning. The proposed convolutional neural network is much smaller than the current state-of-the-art solutions. Nevertheless, the network maintains a high level of accuracy (99.6%), all while using the entire FaceForensics dataset and not including any temporal information. We implement majority voting and show the impact on accuracy (99.67%), where only 1 video of 300 is misclassified. We examine why the model misclassified this one video. In terms of tuning …
Pose Based Human Activity Recognition, Wenbo Li
Pose Based Human Activity Recognition, Wenbo Li
Legacy Theses & Dissertations (2009 - 2024)
Pose based human activity recognition is an important step towards video understanding. The last decade has witnessed the great progress in this field which is driven by multiple technical innovations, i.e., kinect, pose estimation techniques, deep learning, etc.
Poriferal Vision, Saketh Saxena
Poriferal Vision, Saketh Saxena
Master's Projects
Sponges provide nourishment as well as a habitat for various aquatic organisms. Anatomically, sponges are made up of soft tissue with a silica based exoskeleton which serves both as support and protection for the underlying tissue. The exoskeleton persists after the tissue decomposes, and microscopic parts of the exoskeleton break away to form spicules. Oceanographic studies have shown that the density of the sponge spicules is a good indicator of the sponge population in an area. This measure can be used to study sponge population dynamics over time. The spicule density is measured by imaging spicules from samples of water …
Classification Of Humans Into Ayurvedic Prakruti Types Using Computer Vision, Gayatri Gadre
Classification Of Humans Into Ayurvedic Prakruti Types Using Computer Vision, Gayatri Gadre
Master's Projects
Ayurveda, a 5000 years old Indian medical science, believes that the universe and hence humans are made up of five elements namely ether, fire, water, earth, and air. The three Doshas (Tridosha) Vata, Pitta, and Kapha originated from the combinations of these elements. Every person has a unique combination of Tridosha elements contributing to a person’s ‘Prakruti’. Prakruti governs the physiological and psychological tendencies in all living beings as well as the way they interact with the environment. This balance influences their physiological features like the texture and colour of skin, hair, eyes, length of fingers, the shape of the …
Using Computer Vision To Quantify Coral Reef Biodiversity, Niket Bhodia
Using Computer Vision To Quantify Coral Reef Biodiversity, Niket Bhodia
Master's Projects
The preservation of the world’s oceans is crucial to human survival on this planet, yet we know too little to begin to understand anthropogenic impacts on marine life. This is especially true for coral reefs, which are the most diverse marine habitat per unit area (if not overall) as well as the most sensitive. To address this gap in knowledge, simple field devices called autonomous reef monitoring structures (ARMS) have been developed, which provide standardized samples of life from these complex ecosystems. ARMS have now become successful to the point that the amount of data collected through them has outstripped …
Over Speed Detection Using Artificial Intelligence, Samkit Patira
Over Speed Detection Using Artificial Intelligence, Samkit Patira
Master's Projects
Over speeding is one of the most common traffic violations. Around 41 million people are issued speeding tickets each year in USA i.e one every second. Existing approaches to detect over- speeding are not scalable and require manual efforts. In this project, by the use of computer vision and artificial intelligence, I have tried to detect over speeding and report the violation to the law enforcement officer. It was observed that when predictions are done using YoloV3, we get the best results.
Vessel Tree Reconstruction With Divergence Prior, Zhongwen Zhang
Vessel Tree Reconstruction With Divergence Prior, Zhongwen Zhang
Electronic Thesis and Dissertation Repository
Accurate structure analysis of high-resolution 3D biomedical images of vessels is a challenging issue and in demand for medical diagnosis nowadays. Previous curvature regularization based methods [10, 31] give promising results. However, their mathematical models are not designed for bifurcations and generate significant artifacts in such areas. To address the issue, we propose a new geometric regularization principle for reconstructing vector fields based on prior knowledge about their divergence. In our work, we focus on vector fields modeling blood flow pattern that should be divergent in arteries and convergent in veins. We show that this previously ignored regularization constraint can …
Learning To Map The Visual And Auditory World, Tawfiq Salem
Learning To Map The Visual And Auditory World, Tawfiq Salem
Theses and Dissertations--Computer Science
The appearance of the world varies dramatically not only from place to place but also from hour to hour and month to month. Billions of images that capture this complex relationship are uploaded to social-media websites every day and often are associated with precise time and location metadata. This rich source of data can be beneficial to improve our understanding of the globe. In this work, we propose a general framework that uses these publicly available images for constructing dense maps of different ground-level attributes from overhead imagery. In particular, we use well-defined probabilistic models and a weakly-supervised, multi-task training …
Generative Adversarial Networks For Online Visual Object Tracking Systems, Ghsoun Zin
Generative Adversarial Networks For Online Visual Object Tracking Systems, Ghsoun Zin
Theses and Dissertations (Comprehensive)
Object Tracking is one of the essential tasks in computer vision domain as it has numerous applications in various fields, such as human-computer interaction, video surveillance, augmented reality, and robotics. Object Tracking refers to the process of detecting and locating the target object in a series of frames in a video. The state-of-the-art for tracking-by-detection framework is typically made up of two steps to track the target object. The first step is drawing multiple samples near the target region of the previous frame. The second step is classifying each sample as either the target object or the background. Visual object …
Computer Vision-Based Traffic Sign Detection And Extraction: A Hybrid Approach Using Gis And Machine Learning, Zihao Wu
Electronic Theses and Dissertations
Traffic sign detection and positioning have drawn considerable attention because of the recent development of autonomous driving and intelligent transportation systems. In order to detect and pinpoint traffic signs accurately, this research proposes two methods. In the first method, geo-tagged Google Street View images and road networks were utilized to locate traffic signs. In the second method, both traffic signs categories and locations were identified and extracted from the location-based GoPro video. TensorFlow is the machine learning framework used to implement these two methods. To that end, 363 stop signs were detected and mapped accurately using the first method (Google …