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.
Results
Showing 1 to 19 of 19 for “"hand crafted features"”.
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Visual feature learning with application to medical image classification
Various hand-crafted features have been explored for medical image classification, which include SIFT and Local Binary Patterns (LBP). However, hand-crafted features may not be optimally discriminative for classifying images from particular domains (e.g. colonoscopy), as not necessarily tuned to …
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Achieving real-time video summarization on commodity hardware
… the assistance of highly efficient low-level features. A numerical score is then assigned to each segment by our model trained using a set of highperformance hand-crafted features. Finally, segments are selected based on their score to generate a final video summary. On our benchmark dataset, …
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Identifying facial landmarks, action units and emotions using deep networks
… while doing so. Learning the different features of facial images has always been a difficult task and primarily involves using hand-crafted features which would almost definitely ignore some information related to the different dynamics of facial features. We train our network model …
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Novel feature construction technique for detecting anomalous faces and evaluating style transfer methods
… careful design and evaluation of deep-learned features are still necessary like hand-crafted features for computer vision tasks. We demonstrate this in two different domain problems – Anomaly Detection and Style Transfer. We present feature aggregation techniques and also quantitative …
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How deep learning can help emotion recognition
… system either through pre-specified rules or hand-crafted features. However, in the last few years, learned feature representations have experienced a resurgence mainly due to the success of deep neural networks. In this dissertation, we highlight how deep neural networks, when applied to …
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Machine learning applications in plant identification, wireless channel estimation, and gain estimation for multi-user software-defined radio
… images are developed. One of the methods uses hand-crafted features extracted from leaf images to train a support vector machine classifier. The other method combines five publicly available leaf datasets: Flavia, Folio, LeafSnap, Swedish, and Middle European Woods 2014, to create a new data …
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Semi-Supervised Deep Learning Approach for Transportation Mode Identification Using GPS Trajectory Data
… have proposed mode inference models based on hand-crafted features, which might be vulnerable to traffic and environmental conditions. Furthermore, the classification task in almost all models have been performed in a supervised fashion while a large amount of unlabeled GPS trajectories has …
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Machine Learning Methods for Medical and Biological Image Computing
… The current study of computational methods using hand-crafted features does not scale with the increasing number of brain images, hindering the pace of scientific discoveries in neuroscience. In this thesis, I propose computational methods using high-level features for automated analysis of brain …
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Digital Holographic Microscopy for High-throughput Analysis of Tumour Cells
… samples. By analysing and interpreting different features of organoids, cancer-specific signatures are identified. In this thesis, a number of novel contributions are reported. A model-based object presence detection approach exploiting information extracted from a CNN is reported. CNNs are …
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Graph-based Approach for Anomaly Detection in Video Surveillance
… present in the scene. This method utilizes hand-crafted features as well as graphs properties to extract useful information from video sequences. The second part presents an offline framework that uses a one-class classifier to model normal activities represented by spatiotemporal features …
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Automated Building Extraction from Remote Sensing Imagery Using Deep Learning
… building polygon extraction process requires hand-crafted features and high human intervention, which is time-consuming and often has limited generalization capability. In recent years, deep learning-based methods have shed light on the problem with higher levels of automation, segmentation …
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Research on Object Tracking Technology for Orderless and Blurred Movement under Complex Scenes
… is designed to provide supplementary appearance features. A robust similarity measure is proposed to address the outliers caused by motion blurs. Our approach outperforms other approaches in a public benchmark database with motion blurs. (3) An ensemble framework is designed to tackle scale …
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Image Co-saliency Detection and Co-segmentation from The Perspective of Commonalities
… Usually, common objects share similar low-level features, such as appearances, including colours, textures shapes, etc. as well as the high-level semantic features. In this thesis, we explore the commonalities of the common objects in a group of images from low-level features and high-level …
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An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms
… two-tier (computer vs human) approach. Firstly, hand-crafted features were used to ascertain the descriptive nature of a frontal-image and facial profile, for the Pakistani ethnicity. A total of 26 facial landmarks were selected (16 frontal and 10 for the profile) and by incorporating 2 models …
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An Investigation into the Performance of Ethnicity Verification Between Humans and Machine Learning Algorithms
… two-tier (computer vs human) approach. Firstly, hand-crafted features were used to ascertain the descriptive nature of a frontal-image and facial profile, for the Pakistani ethnicity. A total of 26 facial landmarks were selected (16 frontal and 10 for the profile) and by incorporating 2 models …
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Pre-hoc and Post-hoc Diagnosis and Interpretation of Breast Magnetic Resonance Volumes
… for ROIs and the employment of non-optimal hand-crafted features in both stages. These issues have been partially addressed with the introduction of deep learning methods that unfortunately need large strongly annotated training datasets (voxel-wise labelling of each lesion), which tend to …
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Deep neural network models for image classification and regression
… latter are designed/tailored to the problem at hand. This, thereby, raises not only precision concerns but also processing overheads. The success and applicability of a deep learning system relies jointly on both components. In this dissertation, we present innovative deep learning schemes, with …
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Towards a Fast and Accurate Face Recognition System from Deep Representations
… followed by classification or regression. The features representing the input data should have the following desirable properties: 1) they should contain the discriminative information required for accurate classification, 2) they should be robust and adaptive to several variations in the input …
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Re-identification and semantic retrieval of pedestrians in video surveillance scenarios
Person re-identification consists of recognizing individuals across different sensors of a camera network. Whereas clothing appearance cues are widely used, other modalities could be exploited as additional information sources, like anthropometric measures and gait. In this work we investigate …