AIMC Topic: Pattern Recognition, Automated

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Pedestrian attribute recognition using two-branch trainable Gabor wavelets network.

PloS one
Keeping an eye on pedestrians as they navigate through a scene, surveillance cameras are everywhere. With this context, our paper addresses the problem of pedestrian attribute recognition (PAR). This problem entails recognizing attributes such as age...

Artificial Intelligence and Medical Internet of Things Framework for Diagnosis of Coronavirus Suspected Cases.

Journal of healthcare engineering
The world has been facing the COVID-19 pandemic since December 2019. Timely and efficient diagnosis of COVID-19 suspected patients plays a significant role in medical treatment. The deep transfer learning-based automated COVID-19 diagnosis on chest X...

Expression-EEG Bimodal Fusion Emotion Recognition Method Based on Deep Learning.

Computational and mathematical methods in medicine
As one of the key issues in the field of emotional computing, emotion recognition has rich application scenarios and important research value. However, the single biometric recognition in the actual scene has the problem of low accuracy of emotion re...

Learning on knowledge graph dynamics provides an early warning of impactful research.

Nature biotechnology
The scientific ecosystem relies on citation-based metrics that provide only imperfect, inconsistent and easily manipulated measures of research quality. Here we describe DELPHI (Dynamic Early-warning by Learning to Predict High Impact), a framework t...

Multitask feature learning approach for knowledge graph enhanced recommendations with RippleNet.

PloS one
Introducing a knowledge graph into a recommender system as auxiliary information can effectively solve the sparse and cold start problems existing in traditional recommender systems. In recent years, many researchers have performed related work. A re...

A comprehensive swarming intelligent method for optimizing deep learning-based object detection by unmanned ground vehicles.

PloS one
Unmanned ground vehicles (UGVs) are an important research application of artificial intelligence. In particular, the deep learning-based object detection method is widely used in UGV-based environmental perception. Good experimental results are achie...

Feature Selection on Elite Hybrid Binary Cuckoo Search in Binary Label Classification.

Computational and mathematical methods in medicine
For the low optimization accuracy of the cuckoo search algorithm, a new search algorithm, the Elite Hybrid Binary Cuckoo Search (EHBCS) algorithm, is improved by feature weighting and elite strategy. The EHBCS algorithm has been designed for feature ...

Mixed-precision weights network for field-programmable gate array.

PloS one
In this study, we introduced a mixed-precision weights network (MPWN), which is a quantization neural network that jointly utilizes three different weight spaces: binary {-1,1}, ternary {-1,0,1}, and 32-bit floating-point. We further developed the MP...

Artificial intelligence based writer identification generates new evidence for the unknown scribes of the Dead Sea Scrolls exemplified by the Great Isaiah Scroll (1QIsaa).

PloS one
The Dead Sea Scrolls are tangible evidence of the Bible's ancient scribal culture. This study takes an innovative approach to palaeography-the study of ancient handwriting-as a new entry point to access this scribal culture. One of the problems of pa...

Block-cyclic stochastic coordinate descent for deep neural networks.

Neural networks : the official journal of the International Neural Network Society
We present a stochastic first-order optimization algorithm, named block-cyclic stochastic coordinate descent (BCSC), that adds a cyclic constraint to stochastic block-coordinate descent in the selection of both data and parameters. It uses different ...