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Cong Wang, Liyue Wang, Chen Cao, Gang Sun, Yufeng Huang and Sili Zhou
As a core component of an aero-engine, the aerodynamic performance of the nacelle is essential for the overall performance of an aircraft. However, the direct design of a three-dimensional (3D) nacelle is limited by the complex design space consisting of...
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Saidur R. Pavel and Yimin D. Zhang
Massive multiple-input multiple-output (MIMO) technology, which is characterized by the use of a large number of antennas, is a key enabler for the next-generation wireless communication and beyond. Despite its potential for high performance, implementin...
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Fei Ma, Yang Li, Shiguang Ni, Shao-Lun Huang and Lin Zhang
Audio-visual emotion recognition is the research of identifying human emotional states by combining the audio modality and the visual modality simultaneously, which plays an important role in intelligent human-machine interactions. With the help of deep ...
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Ali Reza Sajun and Imran Zualkernan
Given recent advances in deep learning, semi-supervised techniques have seen a rise in interest. Generative adversarial networks (GANs) represent one recent approach to semi-supervised learning (SSL). This paper presents a survey method using GANs for SS...
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Mathias Højgaard Jensen and Stefan Sommer
Computing sample means on Riemannian manifolds is typically computationally costly, as exemplified by computation of the Fréchet mean, which often requires finding minimizing geodesics to each data point for each step of an iterative optimization scheme....
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Ilias Theodorakopoulos, Foteini Fotopoulou and George Economou
In this work, we propose a mechanism for knowledge transfer between Convolutional Neural Networks via the geometric regularization of local features produced by the activations of convolutional layers. We formulate appropriate loss functions, driving a ?...
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Junhyung Kwon and Sangkyun Lee
Despite the advance in deep learning technology, assuring the robustness of deep neural networks (DNNs) is challenging and necessary in safety-critical environments, including automobiles, IoT devices in smart factories, and medical devices, to name a fe...
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Xin Chen and Ying Li
Conventionally, the similarity between two images is measured by the easy-calculating Euclidean distance between their corresponding image feature representations for image retrieval. However, this kind of direct similarity measurement ignores the local ...
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Fayeem Aziz, Aaron S. W. Wong and Stephan Chalup
The aim of manifold learning is to extract low-dimensional manifolds from high-dimensional data. Manifold alignment is a variant of manifold learning that uses two or more datasets that are assumed to represent different high-dimensional representations ...
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