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 26 for “"Feature Fusion"”.
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Heterogeneous Feature Fusion for Visual Recognition
… complicated scenarios, we believe that a single feature is not enough to distinguish web-scale visual concepts. Accordingly, this dissertation proposes to combine heterogeneous features for different visual recognition tasks. We first develop a machinery called Heterogeneous Feature Machines to …
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Cognitive feature fusion for effective pattern recognition in multi-modal images and videos
… popular topics in computer vision, wherein feature extraction and analysis plays an important role. Effective feature descriptors can represent the characteristics of the images and videos, however, for various images and videos, single feature can no longer meet the needs due to its …
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Detection of Fusarium Head Blight on Wheat Spikelets Using a Multi-Scale Feature Fusion CNN Model
… object detection model based on multi-scale feature fusion, specifically designed to detect FHB at the spikelet level in wheat. The proposed model leverages the advanced YOLOv9 framework, integrating the Multi-Scale Feature Enhancement and Fusion (MSFEF) module, to significantly enhance the …
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A Malware Classification Method Based on the Multi-Layer Feature Fusion of Malware Image Representations and Opcode Markov Images
… malware classification method based on the fusion of image representation and opcode features. By integrating the features of image-based malware representation and opcode Markov image, the classification performance is enhanced. Specifically, our model introduces two feature fusion modules: …
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Multimodal Cancelable Biometric System
… biometric verification system, new methods for feature level fusion and feature extraction are proposed, called Cancelable Feature Fusion (CFF) and Cancelable Binary Pattern (CBP), respectively. CFF combines multiple biometric traits using random indexes so that for every fusion it generates a …
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Attention mechanism in deep neural networks for computer vision tasks
… natural language processing for enhancing the feature representation of key sentence fragments over the context. In recent years, the attention mechanism has been widely adopted in solving computer vision tasks by guiding deep neural networks (DNNs) to focus on specific image features for …
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Unified Discriminative Subspace Learning for Multimodality Image Analysis
… applying the local manner in the sample space, feature space, and learning space can sufficiently boost the discriminating power for feature extraction by the subspace learning. As an advanced extension, a learning-locality based subspace learning algorithm for multiple/multimodality feature …
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Fusion Approaches to Individual Tree Species Classification Using Multi-Source Remotely Sensed Data
… topic over the years. This study investigated fusion approaches deployed with Support Vector Machine (SVM) and Random Forest (RF) algorithms to incorporating multispectral imagery (MSI), a very high spatial resolution panchromatic image (PAN), and Light Detection and Ranging (LiDAR) data for …
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Face recognition using multiple features in different color spaces
… recognition, this dissertation applies multiple features derived from the color images instead of the intensity images only. First, this dissertation presents two face recognition methods, which operate in different color spaces, using frequency features by means of Discrete Fourier Transform …
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Profile Modeling in Hierarchical Deep Architecture by Mutual Support
… deep learning structure, called Multi-Features Convolutional Neural Networks (MFCNN), which can comprehensively implement face analysis including age, gender, race and emotion. Moreover, we take the advantages of the mutual support among different facial features from individual tasks …
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Building Footprint Reconstruction from Satellite Imagery Using a Deep Learning Framework with Geometric Regularization
… incorporating geometric regularity, multi-scale feature fusion, and Attraction Field Maps (AFM), the model generates more structured and precise building outlines from a single satellite image. Evaluations on the Wuhan University (WHU) and SpaceNet-2 datasets show that Decoupled-PolyGCN …
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Domain-agnostic named entity recognition on unstructured text
… and show that mere concatenation of external feature vectors with BERT outputs may not train effectively at the recommended low learning rates for BERT. More sophisticated feature fusion is essential.
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Non-speech Acoustic Event Detection Using Multimodal Information
… the thesis emphasizes designing suitable feature representations for different modalities and fusing the information properly. Two cases are studied in this thesis: (1) Acoustic event detection in a meeting room scenario using single-microphone audio cues and single-camera visual cues. …
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Advanced Techniques For Prediction of Forest Above Ground Biomass Using Satellite Remote Sensing Data
… It proposes a method to derive AGB-oriented features and provides a seamless multi-sensor feature fusion method for AGB prediction. The third contribution presents a framework developed from the combination of a hyperparameter optimization procedure and a meta-learning algorithm to set up an …
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Human Detection in the Wild
… information. As the most discriminative features of head and human, face detection has attracted much attention. Despite the great progress that has been achieved for accurate face detection, detecting multi-scale faces, especially for small faces, remains a challenging problem. Existing …
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Methodologies for remaining useful life estimation with multiple sensors in rotating machinery
… on bootstrap sampling. In the current thesis a feature extraction scheme for prognosis is proposed and assessed based on time domain, frequency domain statistical features and Wavelet Packet (WP) energy derived from AE and vibration recordings. ICA is proposed as a preferable fusion technique …
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Deep Learning-based Time Series Forecasting: Models and Applications
… deep learning has efficient automatic feature extraction and robust representation learning capabilities. Using deep learning to enhance time series forecasting performance has become an important research direction. This dissertation studies the point estimation and uncertainty …
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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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