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Chapter and Conference Paper
High-Performance Light Field Reconstruction with Channel-wise and SAI-wise Attention
Light field (LF) images provide rich information and are suitable for high-level computer vision applications. To acquire capabilities of modeling the correlated information of LF, most of the previous method...
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Chapter and Conference Paper
Fast Light Field Reconstruction with Deep Coarse-to-Fine Modeling of Spatial-Angular Clues
Densely-sampled light fields (LFs) are beneficial to many applications such as depth inference and post-capture refocusing. However, it is costly and challenging to capture them. In this paper, we propose a le...
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Chapter and Conference Paper
Using Transfer Learning with Convolutional Neural Networks to Diagnose Breast Cancer from Histopathological Images
Diagnosis from histopathological images is the gold standard in diagnosing breast cancer. This paper investigates using transfer learning with convolutional neural networks to automatically diagnose breast can...
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Chapter and Conference Paper
Using Hidden Markov Model to Predict Human Actions with Swarm Intelligence
This paper proposed a novel algorithm which named Randomized Particle Swarm Optimization (RPSO) to optimize HMM for human activity prediction. The experiments designed in this paper are the classification of h...
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Chapter and Conference Paper
Layer Removal for Transfer Learning with Deep Convolutional Neural Networks
It is usually difficult to find datasets of sufficient size to train Deep Convolutional Neural Networks (DCNNs) from scratch. In practice, a neural network is often pre-trained on a very large source dataset. ...
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Chapter and Conference Paper
Multi-swarm Particle Grid Optimization for Object Tracking
In recent years, one of the popular swarm intelligence algorithm Particle Swarm Optimization has demonstrated to have efficient and accurate outcomes for tracking different object movement. But there are still...
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Chapter and Conference Paper
Hyper-parameter Optimization of Sticky HDP-HMM Through an Enhanced Particle Swarm Optimization
Faced with the problem of uncertainties in object trajectory and pattern recognition in terms of the non-parametric Bayesian approach, we have derived that 2 major methods of optimizing hierarchical Dirichlet ...
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Chapter and Conference Paper
Hybrid Gravitational Search Algorithm with Swarm Intelligence for Object Tracking
This paper proposes a new approach to object tracking using the Hybrid Gravitational Search Algorithm (HGSA). HGSA introduces the Gravitational Search Algorithm (GSA) to the field of object tracking by incorp...
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Chapter and Conference Paper
A New Weight Adjusted Particle Swarm Optimization for Real-Time Multiple Object Tracking
This paper proposes a novel Weight Adjusted Particle Swarm Optimization (WAPSO) to overcome the occlusion problem and computational cost in multiple object tracking. To this end, a new update strategy of inert...
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Chapter and Conference Paper
Feature Selection and Mass Classification Using Particle Swarm Optimization and Support Vector Machine
This paper proposes an effective technique to classify regions of interests (ROIs) of digitized mammograms into mass and normal breast tissue regions by using particle swarm optimization (PSO) based feature se...