Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 31 for “"Bounding boxes"”.
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Segment and Cut: A Simpler Method for Extracting Bounding-Boxes for Object Detection
Object detectors that are based on bounding-box regression are complex and require a lot of refinement to get good results. Is there a simpler way of doing object detection? To that end, I present a new method for object detection where you first segment an image, and then cut each object from the …
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Multiple Bounding Boxes Algorithm in Collision Detection and Its Performances in Sequential VS CUDA Parallel Processing
… in a 2D computer game uses a axisaligned bounding box around each sprite, and checks to determine if the bounding boxes overlap periodically. Using this single bounding box method may result in a large amount of pixel intersection tests, since a sprite may be composed of areas where the …
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System for Collision Detection Between Deformable Models Built on Axis Aligned Bounding Boxes and GPU Based Culling
… Unit (GPU) based culling and Axis Aligned Bounding Box (AABB) based culling. Techniques for performing hierarchy-less GPU-based culling are given. We then discuss how and when to switch between GPU-based culling and AABB based techniques.
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Improved collision detection in StarLogo Nova
… the TightestFitCollider, introduces a variety of bounding spheres, bounding boxes, and bounding capsules as bounding structures that may fit the models in StarLogo Nova more closely. The second system, called the HierarchicalCollider, uses hierarchies of bounding boxes to perform even more precise …
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EdVidParse : detecting people and content in educational videos
… takes an educational video and annotates it with bounding boxes around the people and textual content. EdVidParse uses internal features from deep convolutional neural networks to estimate the bounding boxes, achieving a 0.43 AP score on a test set. Three applications of EdVidParse, including …
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Image-based deep learning approaches for plant phenotyping
… interest were manually annotated as rectangular bounding boxes using the LabelImg tool. The traits were also predicted as rectangular bounding boxes, which were compared with the ground truth bounding boxes in terms of intersection over union metric to evaluate the detection accuracy. The …
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A uniform representation for visual concepts
… manner, with no need for annotated bounding boxes around objects of interest. We encode words as Hidden Markov models such that word models can be composed according to a sentence's semantic structure to efficiently recognize events in videos. We use a discriminative variant of …
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Efficient object detection via structured learning and local classifiers
… to detect object instances ·in images using bounding boxes, which can be trained and tested easily on current personal computers. Our framework is a sliding-window based approach, and consists of two major components: (1) efficient object proposal generation, predicting possible object …
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Depth Correction++ for pseudo-LiDAR
… can provide more information from the 3D bounding boxes, compared to 2D bounding boxes, which can better describe surrounding obstacles with details, providing further help with route planning of autonomous vehicles. Researchers commonly use LiDAR data in 3D object detection, because it …
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Hand detection on images based on deformable part models and additional features
… on an image is made when the system gets a bounding box which overlaps with at least 50% of any ground truth bounding box for a hand on the image. The initial average precision of this detector is around 0.215 compared with a state-of-art of 0.104; however, color and frequency features for …
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Figure Extraction from Scanned Electronic Theses and Dissertations
… 70 scanned ETDs with 3.3k manually annotated bounding boxes for figures and tables. (c) Lastly, we release our entire code and the trained model weights to enable further research (https://github.com/SampannaKahu/deepfigures-open).
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Using UAV Mounted LiDAR to Estimate Plant Height and Growth
… uses a K-means clustering algorithm to find the bounding boxes ofthese clusters, and a voting scheme to determine the best-fit width, height, and orientationof the clusters/plots. This best-fit box is then used to create a grid over the LiDAR dataand the plots are extracted. For pasture, relative …
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Greedy Inference Algorithms for Structured and Neural Models
… Searching for a set of diverse and high-quality bounding boxes. We formulate this problem as the constrained maximization of a monotonic sub-modular function such that there exists a greedy algorithm having near-optimal guarantee. 3) Fill-in-the-blank. The goal is to generate missing words …
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Satellite Image Analysis and Sidewalk Classification using Deep Learning Models
… such as image resizing, image extraction from bounding boxes, and image mapping to actual class label. Due to the class imbalance nature of the dataset, an augmentation technique was employed to augment the minority class and reduce the imbalanced. The data was partitioned into a training (80%) …
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Page segmentation and identification for document image analysis
… the three categories mentioned above using the bounding boxes and horizontal projection. The system has been tested on 215 samples of diverse document types from many sources such as journal articles, magazines, newspapers, facsimiles, and office correspondence. These testing samples include low …
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RNA secondary structure prediction using hybrid methods
… local substructures as pixel-level square bounding boxes. The subsequent stage-2 (S2) models, including the scoring network (S2SC) and the encoder-decoder transformer (S2ED), leverage recurrent neural networks (RNNs) with Dynamic Programming (DP) and an encoder-decoder network with a subset …
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A Deep Learning Approach to the Detection and Tracking of Moving Objects in 2D Point Clouds
… solution, pixel predictions for future-oriented bounding boxes (PIXFOR), combines a CNN with a recurrent network architecture to solve both detection and tracking problems in a single forward pass. Both methods are experimentally validated on an unmanned ground vehicle (UGV) operating on an …
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You Only Look Twice: An Ensemble Deep Learning Model for Wildfire Detection Using Terrestrial Camera Networks
… incipient fires over time, with most containing bounding boxes denoting the approximate location of fire, allowing our system to identify fires quickly while minimizing false positives. Importantly, our spatiotemporal system operates effectively without requiring individual models to rely on …
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Scene understanding with complete scenes and structured representations
… simple representation to parse scenes, mainly bounding boxes and pixel labels, and apply only to visible regions. We believe we should move to deeper levels of scene analysis, embracing more a comprehensive, structured representation. In this dissertation, we focus on analyzing scenes to their …
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Exploring screen summarization with large language and multimodal models
… data such as element types, element text and bounding boxes. Recently, pre-trained large language models (LLMs) and large multimodal models (LMMs) have been shown to have strong performance on various downstream tasks such as sentiment analysis and text classification. Further, LLMs have been …
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