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Section: Publications & Resources
Representation learning is the foundation of machine reading comprehension and inference. In state-of-the-art models, character-level representations have been broadly adopted to alleviate the problem of effectively representing rare or complex words. However, character itself is not a natural minimal linguistic unit for representation or word embedding composing due to ignoring the linguistic coherence of consecutive characters inside word.
Section: Publications & Resources
Automatic speech emotion recognition has been a research hotspot in the field of human-computer interaction over the past decade. However, due to the lack of research on the inherent temporal relationship of the speech waveform, the current recognition accuracy needs improvement.
Section: Publications & Resources
Short duration text-independent speaker verification remains a hot research topic in recent years, and deep neural network based embeddings have shown impressive results in such conditions. Good speaker embeddings require the property of both small intra-class variation and large inter-class difference, which is critical for the ability of discrimination and generalization.
Section: Publications & Resources
Publication: IEEE Transactions on Computational Imaging
Coded illumination can enable quantitative phase microscopy of transparent samples with minimal hardware requirements. Intensity images are captured with different source patterns, then a nonlinear phase retrieval optimization reconstructs the image. The nonlinear nature of the processing makes optimizing the illumination pattern designs complicated.
Section: Publications & Resources
Publication: IEEE Transactions on Computational Imaging
Dictionary learning for sparse representations is generally conducted in two alternating steps-sparse coding and dictionary updating. In this paper, a new approach to solve the sparse coding step is proposed. Because this step involves an ℓ0 -norm, most, if not all, existing solutions only provide a local or approximate solution. Instead, a real ℓ0 optimization is considered for the sparse coding problem providing a global solution.
Section: Publications & Resources
Publication: IEEE Transactions on Computational Imaging
Resolution enhancements are often desired in imaging applications where high-resolution sensor arrays are difficult to obtain. Many computational imaging methods have been proposed to encode high-resolution scene information on low-resolution sensors by cleverly modulating light from the scene before it hits the sensor.
Section: Publications & Resources
Publication: IEEE Transactions on Image Processing
Image classification is an essential and challenging task in computer vision. Despite its prevalence, the combination of the deep convolutional neural network (DCNN) and the Fisher vector (FV) encoding method has limited performance since the class-irrelevant background used in the traditional FV encoding may result in less discriminative image features.
Section: Publications & Resources
Publication: IEEE Transactions on Image Processing
We study the problem of image alignment for panoramic stitching. Unlike most existing approaches that are feature-based, our algorithm works on pixels directly, and accounts for errors across the whole images globally. Technically, we formulate the alignment problem as rank-1 and sparse matrix decomposition over transformed images, and develop an efficient algorithm for solving this challenging non-convex optimization problem.
Section: Publications & Resources
Publication: IEEE Transactions on Image Processing
We present a novel global non-rigid registration method for dynamic 3D objects. Our method allows objects to undergo large non-rigid deformations and achieves high-quality results even with substantial pose change or camera motion between views. In addition, our method does not require a template prior and uses less raw data than tracking-based methods since only a sparse set of scans is needed.
Immediate opening for a postdoctoral researcher in radionavigation and wireless communication systems at the Autonomous Systems Perception, Intelligence, & Navigation Laboratory (https://aspin.ucr.edu); University of California, Irvine (https://uci.edu).
