AIMC Topic: Recognition, Psychology

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Configurable Graph Reasoning for Visual Relationship Detection.

IEEE transactions on neural networks and learning systems
Visual commonsense knowledge has received growing attention in the reasoning of long-tailed visual relationships biased in terms of object and relation labels. Most current methods typically collect and utilize external knowledge for visual relations...

Multi-Stage Feature Extraction and Classification for Ship-Radiated Noise.

Sensors (Basel, Switzerland)
Due to the complexity and unique features of the hydroacoustic channel, ship-radiated noise (SRN) detected using a passive sonar tends mostly to distort. SRN feature extraction has been proposed to improve the detected passive sonar signal. Unfortuna...

A Study of Two-Way Short- and Long-Term Memory Network Intelligent Computing IoT Model-Assisted Home Education Attention Mechanism.

Computational intelligence and neuroscience
This paper analyzes and collates the research on traditional homeschooling attention mechanism and homeschooling attention mechanism based on two-way short- and long-term memory network intelligent computing IoT model and finds the superiority of two...

Biological convolutions improve DNN robustness to noise and generalisation.

Neural networks : the official journal of the International Neural Network Society
Deep Convolutional Neural Networks (DNNs) have achieved superhuman accuracy on standard image classification benchmarks. Their success has reignited significant interest in their use as models of the primate visual system, bolstered by claims of thei...

Deep Learning Based Air-Writing Recognition with the Choice of Proper Interpolation Technique.

Sensors (Basel, Switzerland)
The act of writing letters or words in free space with body movements is known as air-writing. Air-writing recognition is a special case of gesture recognition in which gestures correspond to characters and digits written in the air. Air-writing, unl...

Food Image Recognition and Food Safety Detection Method Based on Deep Learning.

Computational intelligence and neuroscience
With the development of machine learning, as a branch of machine learning, deep learning has been applied in many fields such as image recognition, image segmentation, video segmentation, and so on. In recent years, deep learning has also been gradua...

Complex Deep Neural Networks from Large Scale Virtual IMU Data for Effective Human Activity Recognition Using Wearables.

Sensors (Basel, Switzerland)
Supervised training of human activity recognition (HAR) systems based on body-worn inertial measurement units (IMUs) is often constrained by the typically rather small amounts of labeled sample data. Systems like IMUTube have been introduced that emp...

An Efficient Human Instance-Guided Framework for Video Action Recognition.

Sensors (Basel, Switzerland)
In recent years, human action recognition has been studied by many computer vision researchers. Recent studies have attempted to use two-stream networks using appearance and motion features, but most of these approaches focused on clip-level video ac...

Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network.

Sensors (Basel, Switzerland)
UNLABELLED: Background and motivation: Every year, millions of Muslims worldwide come to Mecca to perform the Hajj. In order to maintain the security of the pilgrims, the Saudi government has installed about 5000 closed circuit television (CCTV) came...

A Novel Hybrid Deep Learning Model for Human Activity Recognition Based on Transitional Activities.

Sensors (Basel, Switzerland)
In recent years, a plethora of algorithms have been devised for efficient human activity recognition. Most of these algorithms consider basic human activities and neglect postural transitions because of their subsidiary occurrence and short duration....