Results 191 to 200 of about 530,497 (220)
A lightweight network for traffic sign detection via multiple scale context awareness and semantic information guidance. [PDF]
Sci RepDu C, Su S, Lin C, Yao Y, Jin R, Hong X.
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A lightweight network architecture for traffic sign recognition based on enhanced LeNet-5 network. [PDF]
Front NeurosciAn Y, Yang C, Zhang S.
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Traffic Sign Recognition Using Multi-Task Deep Learning for Self-Driving Vehicles. [PDF]
Sensors (Basel)Alawaji K, Hedjar R, Zuair M.
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A Vision-Language Model-Based Traffic Sign Detection Method for High-Resolution Drone Images: A Case Study in Guyuan, China. [PDF]
Sensors (Basel)Yao J +6 more
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Reducing Training Data Using Pre-Trained Foundation Models: A Case Study on Traffic Sign Segmentation Using the Segment Anything Model. [PDF]
J ImagingHenninger S +3 more
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YOLOv7-TS: A Traffic Sign Detection Model Based on Sub-Pixel Convolution and Feature Fusion. [PDF]
Sensors (Basel)Zhao S, Yuan Y, Wu X, Wang Y, Zhang F.
europepmc +1 more source
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2011
To detect and classify objects contained in real images, acquired in unconstrained environments, is a challenging problem in computer vision, which complexity makes unfeasible the design of handcrafted solutions. In this chapter, the object detection problem is introduced, highlighting the main issues and challenges, and providing a basic introduction ...
Sergio Escalera +4 more
openaire +1 more source
To detect and classify objects contained in real images, acquired in unconstrained environments, is a challenging problem in computer vision, which complexity makes unfeasible the design of handcrafted solutions. In this chapter, the object detection problem is introduced, highlighting the main issues and challenges, and providing a basic introduction ...
Sergio Escalera +4 more
openaire +1 more source
2017
Object detection is one of the hard problems in computer vision. It gets even harder in time demanding tasks such as ADAS. In this chapter, we explained a convolutional neural network that is able to analyze high-resolution images in real time and it accurately finds traffic signs.
Hamed Habibi Aghdam, Elnaz Jahani Heravi
openaire +1 more source
Object detection is one of the hard problems in computer vision. It gets even harder in time demanding tasks such as ADAS. In this chapter, we explained a convolutional neural network that is able to analyze high-resolution images in real time and it accurately finds traffic signs.
Hamed Habibi Aghdam, Elnaz Jahani Heravi
openaire +1 more source
2011
Since the initials of Artificial Intelligence, many learning techniques have been proposed to deal with many artificial systems. The initial learning designs were proposed to deal with just two classes. Which option is the best one given two previous possibilities?
Sergio Escalera +4 more
openaire +1 more source
Since the initials of Artificial Intelligence, many learning techniques have been proposed to deal with many artificial systems. The initial learning designs were proposed to deal with just two classes. Which option is the best one given two previous possibilities?
Sergio Escalera +4 more
openaire +1 more source