A review of convolutional neural network architectures and their optimizations
The research advances concerning the typical architectures of convolutional neural
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …
networks (CNNs) as well as their optimizations are analyzed and elaborated in detail in this …
Model compression and hardware acceleration for neural networks: A comprehensive survey
Domain-specific hardware is becoming a promising topic in the backdrop of improvement
slow down for general-purpose processors due to the foreseeable end of Moore's Law …
slow down for general-purpose processors due to the foreseeable end of Moore's Law …
Rethinking bottleneck structure for efficient mobile network design
The inverted residual block is dominating architecture design for mobile networks recently. It
changes the classic residual bottleneck by introducing two design rules: learning inverted …
changes the classic residual bottleneck by introducing two design rules: learning inverted …
Tensor methods in computer vision and deep learning
Tensors, or multidimensional arrays, are data structures that can naturally represent visual
data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic …
data of multiple dimensions. Inherently able to efficiently capture structured, latent semantic …
A survey on green deep learning
In recent years, larger and deeper models are springing up and continuously pushing state-
of-the-art (SOTA) results across various fields like natural language processing (NLP) and …
of-the-art (SOTA) results across various fields like natural language processing (NLP) and …
Automated detection of Parkinson's disease based on multiple types of sustained phonations using linear discriminant analysis and genetically optimized neural …
Objective: Parkinson's disease (PD) is a serious neurodegenerative disorder. It is reported
that most of PD patients have voice impairments. But these voice impairments are not …
that most of PD patients have voice impairments. But these voice impairments are not …
Early diagnosis of Parkinson's disease from multiple voice recordings by simultaneous sample and feature selection
Parkinson's disease (PD) is a serious neurodegenerative disorder. It is reported that more
than 90% of PD patients have voice impairments. Multiple types of voice recordings have …
than 90% of PD patients have voice impairments. Multiple types of voice recordings have …
High-order tensor flow processing using integrated photonic circuits
Tensor analytics lays the mathematical basis for the prosperous promotion of multiway
signal processing. To increase computing throughput, mainstream processors transform …
signal processing. To increase computing throughput, mainstream processors transform …
Low rank tensor completion for multiway visual data
Tensor completion recovers missing entries of multiway data. The missing of entries could
often be caused during the data acquisition and transformation. In this paper, we provide an …
often be caused during the data acquisition and transformation. In this paper, we provide an …
Multiplex transformed tensor decomposition for multidimensional image recovery
Low-rank tensor completion aims to recover the missing entries of multi-way data, which has
become popular and vital in many fields such as signal processing and computer vision. It …
become popular and vital in many fields such as signal processing and computer vision. It …