Real Time object recognition is the major classification method used in many authentication and recognition applications. But it becomes difficult to identify the object when the input object image is ...

Consider the case of detecting simple visual features that show no variation, e.g., edges of different orientations. ... (ERC-2010-StG 261352), and by the Human Brain Project (EU grant 604102 ...

The proposed model exploits the convolutional neural network to extract the detailed feature information of the object in the infrared image. Then, it uses the 2DPCANet screening mechanism to reduce ...

"We propose an object detection system that relies on a multi-region deep convolutional neural network (CNN) that also encodes semantic segmentation-aware features. The resulting CNN-based ...

Some of the popular model architectures for object recognition are Faster R-CNN, YOLO, Mask R-CNN, and U-Net. You should compare their performance, speed, and accuracy on your data and choose the ...

FFRA-Net is a feature fusion network designed to address the recognition of obscured facial expressions. The method comprises a multi-scale module, a local attention module, a feature fusion module, ...

Public Library of Science. (2007, August 9). How Dynamic Brain Networks Enable Object Recognition. ScienceDaily. Retrieved June 3, 2025 from www.sciencedaily.com / releases / 2007 / 08 ...

This repository contains the implementation of synthetic sequential point cloud dataset generation and the implementation of hybrid learning architecture, comparises of generative autoencoder and the ...