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Visual Perception

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The -MDA: An Invariant to Shifting, Scaling, and Rotating Variance for 3D Object Recognition Using Diffractive Deep Neural Network.

Sensors (Basel, Switzerland)
The diffractive deep neural network (DNN) can efficiently accomplish 2D object recognition based on rapid optical manipulation. Moreover, the multiple-view DNN array (MDA) possesses the obvious advantage of being able to effectively achieve 3D object...

MRBENet: A Multiresolution Boundary Enhancement Network for Salient Object Detection.

Computational intelligence and neuroscience
Salient Object Detection (SOD) simulates the human visual perception in locating the most attractive objects in the images. Existing methods based on convolutional neural networks have proven to be highly effective for SOD. However, in some cases, th...

Visual Information Computing and Processing Model Based on Artificial Neural Network.

Computational intelligence and neuroscience
This paper analyzes the parallel and serial information processing structure of visual system and proposes a visual information processing model with three layers: visual receptor layer, visual information conduction and relay layer, and information ...

A Smart Alcoholmeter Sensor Based on Deep Learning Visual Perception.

Sensors (Basel, Switzerland)
Process automation, in general, enables the enhancement of productivity, product quality, and consistency alongside other production metrics. Liquor production on an industrial scale also follows the automation trend. However, small and medium produc...

General object-based features account for letter perception.

PLoS computational biology
After years of experience, humans become experts at perceiving letters. Is this visual capacity attained by learning specialized letter features, or by reusing general visual features previously learned in service of object categorization? To explore...

Understanding transformation tolerant visual object representations in the human brain and convolutional neural networks.

NeuroImage
Forming transformation-tolerant object representations is critical to high-level primate vision. Despite its significance, many details of tolerance in the human brain remain unknown. Likewise, despite the ability of convolutional neural networks (CN...

A Review of Multi-Modal Learning from the Text-Guided Visual Processing Viewpoint.

Sensors (Basel, Switzerland)
For decades, co-relating different data domains to attain the maximum potential of machines has driven research, especially in neural networks. Similarly, text and visual data (images and videos) are two distinct data domains with extensive research ...

MouseNet: A biologically constrained convolutional neural network model for the mouse visual cortex.

PLoS computational biology
Convolutional neural networks trained on object recognition derive inspiration from the neural architecture of the visual system in mammals, and have been used as models of the feedforward computation performed in the primate ventral stream. In contr...

Massive-Scale Aerial Photo Categorization by Cross-Resolution Visual Perception Enhancement.

IEEE transactions on neural networks and learning systems
Categorizing aerial photographs with varied weather/lighting conditions and sophisticated geomorphic factors is a key module in autonomous navigation, environmental evaluation, and so on. Previous image recognizers cannot fulfill this task due to thr...

Infrared and Visible Image Fusion Method Using Salience Detection and Convolutional Neural Network.

Sensors (Basel, Switzerland)
This paper presents an algorithm for infrared and visible image fusion using significance detection and Convolutional Neural Networks with the aim of integrating discriminatory features and improving the overall quality of visual perception. Firstly,...