AIMC Topic: Visual Perception

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A Study on Object Detection Performance of YOLOv4 for Autonomous Driving of Tram.

Sensors (Basel, Switzerland)
Recently, autonomous driving technology has been in the spotlight. However, autonomous driving is still in its infancy in the railway industry. In the case of railways, there are fewer control elements than autonomous driving of cars due to the chara...

Understanding Human Object Vision: A Picture Is Worth a Thousand Representations.

Annual review of psychology
Objects are the core meaningful elements in our visual environment. Classic theories of object vision focus upon object recognition and are elegant and simple. Some of their proposals still stand, yet the simplicity is gone. Recent evolutions in beha...

On the role of feedback in image recognition under noise and adversarial attacks: A predictive coding perspective.

Neural networks : the official journal of the International Neural Network Society
Brain-inspired machine learning is gaining increasing consideration, particularly in computer vision. Several studies investigated the inclusion of top-down feedback connections in convolutional networks; however, it remains unclear how and when thes...

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 ...