AIMC Topic: Pattern Recognition, Automated

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ScatT-LOOP: scattering tetrolet-LOOP descriptor and optimized NN for iris recognition at-a-distance.

Biomedizinische Technik. Biomedical engineering
Iris Recognition at-a Distance (IAAD) is a major challenge for researchers due to the defects associated with the visual imaging and poor image quality in dynamic environments, which imposed bad impacts on the accuracy of recognition. Thus, in order ...

Self-augmentation: Generalizing deep networks to unseen classes for few-shot learning.

Neural networks : the official journal of the International Neural Network Society
Few-shot learning aims to classify unseen classes with a few training examples. While recent works have shown that standard mini-batch training with carefully designed training strategies can improve generalization ability for unseen classes, well-kn...

Improved deep CNNs based on Nonlinear Hybrid Attention Module for image classification.

Neural networks : the official journal of the International Neural Network Society
Recent years have witnessed numerous successful applications of incorporating attention module into feed-forward convolutional neural networks. Along this line of research, we design a novel lightweight general-purpose attention module by simultaneou...

Giant Panda Identification.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The lack of automatic tools to identify giant panda makes it hard to keep track of and manage giant pandas in wildlife conservation missions. In this paper, we introduce a new Giant Panda Identification (GPID) task, which aims to identify each indivi...

Fast semantic segmentation method for machine vision inspection based on a fewer-parameters atrous convolution neural network.

PloS one
Owing to the recent development in deep learning, machine vision has been widely used in intelligent manufacturing equipment in multiple fields, including precision-manufacturing production lines and online product-quality inspection. This study aims...

A Novel Learning Algorithm to Optimize Deep Neural Networks: Evolved Gradient Direction Optimizer (EVGO).

IEEE transactions on neural networks and learning systems
Gradient-based algorithms have been widely used in optimizing parameters of deep neural networks' (DNNs) architectures. However, the vanishing gradient remains as one of the common issues in the parameter optimization of such networks. To cope with t...

Dynamical Channel Pruning by Conditional Accuracy Change for Deep Neural Networks.

IEEE transactions on neural networks and learning systems
Channel pruning is an effective technique that has been widely applied to deep neural network compression. However, many existing methods prune from a pretrained model, thus resulting in repetitious pruning and fine-tuning processes. In this article,...

Robust Environmental Sound Recognition With Sparse Key-Point Encoding and Efficient Multispike Learning.

IEEE transactions on neural networks and learning systems
The capability for environmental sound recognition (ESR) can determine the fitness of individuals in a way to avoid dangers or pursue opportunities when critical sound events occur. It still remains mysterious about the fundamental principles of biol...

A Review of the Discriminant Analysis Methods for Food Quality Based on Near-Infrared Spectroscopy and Pattern Recognition.

Molecules (Basel, Switzerland)
Near-infrared spectroscopy (NIRS) combined with pattern recognition technique has become an important type of non-destructive discriminant method. This review first introduces the basic structure of the qualitative analysis process based on near-infr...

Bilateral attention decoder: A lightweight decoder for real-time semantic segmentation.

Neural networks : the official journal of the International Neural Network Society
The encoder-decoder structure has been introduced into semantic segmentation to improve the spatial accuracy of the network by fusing high- and low-level feature maps. However, recent state-of-the-art encoder-decoder-based methods can hardly attain t...