Searched for: subject%3A%22Computer%255C+vision%22
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Liu, X. (author)
Deep learning is the core algorithmic tool for automatically processing large amounts of data. Deep learning models are defined as a stack of functions (called layers) with millions of parameters, that are updated during training by fitting them to data. Deep learning models have show remarkable accuracy gains on visual problems in video and...
doctoral thesis 2024
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Lengyel, A. (author)
Computer vision algorithms are getting more advanced by the day and slowly approach human-like capabilities, such as detecting objects in cluttered scenes and recognizing facial expressions. Yet, computers learn to perform these tasks very differently from humans. Where humans can generalize between different lighting conditions or geometric...
doctoral thesis 2024
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Lee, Y. (author)
E-learning has shifted the traditional learning paradigms in higher education, offering more flexible, ubiquitous, and personalized learning experiences. The previous years COVID-19 pandemic required a re-calibration of education to accommodate virtual learning environments from the traditional classroom-based education. Widespread learning...
doctoral thesis 2024
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Hazelaar, Sander (author)
New insights into the landing behavior of bumblebees show an adaptive strategy where the optical flow expansion of the landing target is step-wise regulated. In this article, the potential benefits of this approach are studied by replicating the landing experiment with a quadrotor. To this end, an open-loop switching method is developed,...
master thesis 2024
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Kuhn, Emanuel (author)
Existing content-based image retrieval models work well for natural photos, but not for images of architectural floor plans. <br/>Previous work on floor plan retrieval has focused on graph-based methods, rather than image-based floor plans.<br/>Training a CNN-based representation learning framework on segmented floor plan images with standard...
master thesis 2024
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Esteves Henriques, Bernardo (author)
Search and Rescue (SaR) missions present challenges due to the complexity of the disaster scenarios. Most life losses and injuries occur in developing countries. Robotics has become indispensable for rapidly locating disaster victims. Combining flying and ground robots more effectively serves this purpose due to their complementary features. To...
master thesis 2024
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Bier, H.H. (author), Hidding, A.J. (author), Khademi, S. (author), van Engelenburg, C.C.J. (author), Prendergast, J.M. (author), Peternel, L. (author)
Real-world applications of Artificial Intelligence (AI) in architecture have been explored more recently at Technical University (TU) Delft by integrating AI in Design-to-Robotic-Production-Assembly and -Operation (D2RPA&amp;O) methods. These embed robotics into building processes and buildings by linking computational design with robotic...
conference paper 2024
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Garofano, V. (author), Hepworth, M. (author), Shahin, R. (author), Pang, Y. (author), Negenborn, R.R. (author)
In this study, we investigated autonomous vessel obstacle avoidance using advanced techniques within the Guidance, Navigation, and Control (GNC) framework. We propose a Mixed Integer Linear Programming (MILP) based Guidance system for robust path planning avoiding static and dynamic obstacles. For Navigation, we suggest a multi-modal neural...
journal article 2024
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Fung-A-Jou, Xavier (author)
Piping and Instrumentation Diagrams (P&amp;IDs) are graphical representations utilized in chemical engineering plants. Due to confidentiality reasons and legacy drawings, these diagrams are sent in PDF format. Piping engineers need to make a material take-off (MTO), a document containing all the components of a P&amp;ID from these drawings....
master thesis 2023
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Fanizza, Vincenzo (author)
Performing crucial activities for space exploration, e.g., debris removal and on-orbit servicing, systems for Rendezvous and Proximity Operations (RPO) are required to be autonomous and scalable. Within this context, learning-based relative navigation has gained significant traction due to the latest advancements in AI and the cost-effectiveness...
master thesis 2023
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Xu, Chenghao (author)
In recent years, visual Simultaneous Localization and Mapping (SLAM) have gained significant attention and found wide-ranging applications in diverse scenarios. Recent advances in computer vision and deep learning also enrich visual SLAM capabilities in scene understanding and large-scale operation. However, despite remarkable performance in...
master thesis 2023
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Basting, Mark (author)
In real-life scenarios, there are many variations in sizes of objects of the same category and the objects are not always placed at a fixed distance from the camera. This results in objects taking up an arbitrary size of pixels in the image. Vanilla CNNs are by design only translation equivariant and thus have to learn separate filters for...
master thesis 2023
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Tolsma, Pieter (author)
Transparency and specularity are challenging phenomena that modern depth perception systems have to deal with in order to be used in practice. A promising family of depth estimation methods is Multi-View Stereo (MVS), which combines multiple RGB images to predict depth, thus circumventing the need for costly specialized hardware. Although...
master thesis 2023
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van den Berg, Jasper (author)
The traumatic loss of a hand is a horrific experience usually followed by significant psychological, functional and rehabilitation challenges. Even though much progress has been made in the past decades, the prosthetic challenge of restoring the human hand functionality is still far from being achieved. Autonomous prosthetic hands showed...
master thesis 2023
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van den Bent, Luuk (author)
master thesis 2023
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Marinos, Marios (author)
Emotion recognition is a challenging problem in the field of computer vision. The automatic classification of emotions using facial expressions is a promising approach to understand human behavior in various applications such as marketing, health, and education. How- ever, recognizing some emotions, such as anger, jealousy, contempt, and disgust...
master thesis 2023
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Karnani, Simran (author)
In recent years, there has been a growing interest among researchers in the explainability, fairness, and robustness of Computer Vision models. While studies have explored the usability of these models for end users, limited research has delved into the challenges and requirements faced by researchers investigating these requirements. This study...
master thesis 2023
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Haarman, Luuk (author)
Convolutional Neural Networks (CNNs) benefit from fine-grained details in high-resolution images, but these images are not always easily available as data collection can be expensive or time-consuming. Transfer learning pre-trains models on data from a related domain before fine-tuning on the main domain, and is a common strategy to deal with...
master thesis 2023
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Sharma, Anirvin (author)
Image data augmentation has been regarded as a reliable and effective way to increase the data available for training. With the advent and rise of Generative AI, generative data augmentation has been shown to realize even better gains in performance for downstream tasks. However, these performance gains are often the cause of "extra information"...
master thesis 2023
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Masouris, Thanos (author)
Chess recognition refers to the task of identifying the chess pieces configuration from a chessboard image. Contrary to the predominant approach that aims to solve this task through the pipeline of chessboard detection, square localization, and piece classification, we rely on the power of deep learning models and introduce two novel...
master thesis 2023
Searched for: subject%3A%22Computer%255C+vision%22
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