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Pattern Recognition, Automated

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Learning image features with fewer labels using a semi-supervised deep convolutional network.

Neural networks : the official journal of the International Neural Network Society
Learning feature embeddings for pattern recognition is a relevant task for many applications. Deep learning methods such as convolutional neural networks can be employed for this assignment with different training strategies: leveraging pre-trained m...

Clustering Ensemble Model Based on Self-Organizing Map Network.

Computational intelligence and neuroscience
This paper proposes a clustering ensemble method that introduces cascade structure into the self-organizing map (SOM) to solve the problem of the poor performance of a single clusterer. Cascaded SOM is an extension of classical SOM combined with the ...

WiGAN: A WiFi Based Gesture Recognition System with GANs.

Sensors (Basel, Switzerland)
In recent years, a series of research experiments have been conducted on WiFi-based gesture recognition. However, current recognition systems are still facing the challenge of small samples and environmental dependence. To deal with the problem of pe...

Improved dual-scale residual network for image super-resolution.

Neural networks : the official journal of the International Neural Network Society
In recent years, convolutional neural networks have been successfully applied to single image super-resolution (SISR) tasks, making breakthrough progress both in accuracy and speed. In this work, an improved dual-scale residual network (IDSRN), achie...

A Predictive-Coding Network That Is Both Discriminative and Generative.

Neural computation
Predictive coding (PC) networks are a biologically interesting class of neural networks. Their layered hierarchy mimics the reciprocal connectivity pattern observed in the mammalian cortex, and they can be trained using local learning rules that appr...

Image Target Recognition via Mixed Feature-Based Joint Sparse Representation.

Computational intelligence and neuroscience
An image target recognition approach based on mixed features and adaptive weighted joint sparse representation is proposed in this paper. This method is robust to the illumination variation, deformation, and rotation of the target image. It is a data...

Twin minimax probability machine for pattern classification.

Neural networks : the official journal of the International Neural Network Society
We propose a new distribution-free Bayes optimal classifier, called the twin minimax probability machine (TWMPM), which combines the benefits of both minimax probability machine(MPM) and twin support vector machine (TWSVM). TWMPM tries to construct t...

Design and Performance Evaluation of a Deep Neural Network for Spectrum Recognition of Underwater Targets.

Computational intelligence and neuroscience
Due to the complexity of the underwater environment, underwater acoustic target recognition (UATR) has always been challenging. Although deep neural networks (DNN) have been used in UATR and some achievements have been made, the performance is not sa...

A New Image Classification Approach via Improved MobileNet Models with Local Receptive Field Expansion in Shallow Layers.

Computational intelligence and neuroscience
Because deep neural networks (DNNs) are both memory-intensive and computation-intensive, they are difficult to apply to embedded systems with limited hardware resources. Therefore, DNN models need to be compressed and accelerated. By applying depthwi...