FOREIGN OBJECT DETECTION IN TV AND LWIR IMAGERY OF A RUNWAY BY DEEP CONVOLUTIONAL NEURAL NETWORKS

2017 ◽  
Vol 9 (4) ◽  
pp. 89-96
Author(s):  
V.V. Kniaz ◽  
V.V. Fedorenko ◽  
V.A. Mizginov ◽  
V.A. Knyaz ◽  
W. Purgathofer
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Convolutional Neural Networks ◽  
Foreign Object ◽  
Deep Convolutional Neural Networks

scholarly journals Identification of Tomato Disease Types and Detection of Infected Areas Based on Deep Convolutional Neural Networks and Object Detection Techniques

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Qimei Wang ◽  
Feng Qi ◽  
Minghe Sun ◽  
Jianhua Qu ◽  
Jie Xue
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Convolutional Neural Networks ◽  
Detection Methods ◽  
Disease Detection ◽  
Deep Convolutional Neural Networks ◽  
Detection Techniques ◽  
Tomato Diseases ◽  
Validation Set ◽  
Tomato Disease

This study develops tomato disease detection methods based on deep convolutional neural networks and object detection models. Two different models, Faster R-CNN and Mask R-CNN, are used in these methods, where Faster R-CNN is used to identify the types of tomato diseases and Mask R-CNN is used to detect and segment the locations and shapes of the infected areas. To select the model that best fits the tomato disease detection task, four different deep convolutional neural networks are combined with the two object detection models. Data are collected from the Internet and the dataset is divided into a training set, a validation set, and a test set used in the experiments. The experimental results show that the proposed models can accurately and quickly identify the eleven tomato disease types and segment the locations and shapes of the infected areas.

An energy-efficient deep convolutional neural networks coprocessor for multi-object detection

2020 ◽  
Vol 98 ◽  
pp. 104737
Author(s):  
Yuancong Wu ◽  
J.J. Wang ◽  
Kun Qian ◽  
Yanchen Liu ◽  
Rui Guo ◽  
...  
Keyword(s):  
Neural Networks ◽  
Object Detection ◽  
Convolutional Neural Networks ◽  
Energy Efficient ◽  
Deep Convolutional Neural Networks
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