scholarly journals Vehicle Detection in Aerial Images Based on 3D Depth Maps and Deep Neural Networks

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Saleh Javadi ◽  
Mattias Dahl ◽  
Mats I. Pettersson
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Vehicle Detection ◽  
Aerial Images ◽  
Depth Maps

scholarly journals Avaliação do Processo para Embarcar uma Rede Neural Baseada em YOLO Utilizando um Acelerador de Hardware Dedicado

2020 ◽  
Author(s):  
Isabel Costa ◽  
Elias Silva Jr ◽  
Antônio Rodrigues ◽  
Leandro Angeloni ◽  
Edmilson Dias
Keyword(s):  
Neural Networks ◽  
Computer Vision ◽  
Object Detection ◽  
Power Distribution ◽  
Deep Neural Networks ◽  
Aerial Images ◽  
Great Progress ◽  
Operational Networks

Object Detection is a challenging task in computer vision, but Deep Neural Networks (DNN) have made great progress in this area. This work presents the process and the results obtained in the attempts to embed a YOLO V3 model in a Neural Compute Engine, the Movidius Stick. Experiments were carried out with a Tensorflow model that is converted to Movidius (using OpenVINO) including an evaluation of the Movidius stick connected to a Raspberry Pi3. The application uses aerial images of power distribution towers captured by a drone. Although there are some fully operational networks for Neural Compute Engines, there are some difficulties in porting new networks to the platform, with gains in performance, but with losses in accuracy.

scholarly journals Bio-Inspired Foveated Technique for Augmented-Range Vehicle Detection Using Deep Neural Networks

2019 ◽  
Author(s):  
Pedro Azevedo ◽  
Sabrina S. Panceri ◽  
Ranik Guidolini ◽  
Vinicius B. Cardoso ◽  
Claudine Badue ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Vehicle Detection
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