Deep CNN Based Automatic Detection and Identification of Bengal Tigers

2021 ◽  
pp. 189-198
Author(s):  
Tarun Kishore ◽  
Aditya Jha ◽  
Saurav Kumar ◽  
Suman Bhattacharya ◽  
Mahamuda Sultana
Keyword(s):  
Automatic Detection ◽  
Detection And Identification ◽  
Deep Cnn

scholarly journals Automatic Detection of Discrimination Actions from Social Images

Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 325
Author(s):  
Zhihao Wu ◽  
Baopeng Zhang ◽  
Tianchen Zhou ◽  
Yan Li ◽  
Jianping Fan
Keyword(s):  
Action Recognition ◽  
State Of The Art ◽  
Automatic Detection ◽  
Experimental Results ◽  
Practical Approach ◽  
Detection And Identification ◽  
Art Methods ◽  
Image Set ◽  
Social Images ◽  
Relationship Identification

In this paper, we developed a practical approach for automatic detection of discrimination actions from social images. Firstly, an image set is established, in which various discrimination actions and relations are manually labeled. To the best of our knowledge, this is the first work to create a dataset for discrimination action recognition and relationship identification. Secondly, a practical approach is developed to achieve automatic detection and identification of discrimination actions and relationships from social images. Thirdly, the task of relationship identification is seamlessly integrated with the task of discrimination action recognition into one single network called the Co-operative Visual Translation Embedding++ network (CVTransE++). We also compared our proposed method with numerous state-of-the-art methods, and our experimental results demonstrated that our proposed methods can significantly outperform state-of-the-art approaches.

scholarly journals An Overview of Challenges Associated with Automatic Detection of Concrete Cracks in the Presence of Shadows

2021 ◽  
Vol 11 (23) ◽  
pp. 11396
Author(s):  
Mayur Pal ◽  
Paulius Palevičius ◽  
Mantas Landauskas ◽  
Ugnė Orinaitė ◽  
Inga Timofejeva ◽  
...  
Keyword(s):  
Crack Detection ◽  
Automatic Detection ◽  
High Accuracy ◽  
Automated Detection ◽  
Detection Accuracy ◽  
Shadow Removal ◽  
Engineering Structures ◽  
Popular Approach ◽  
Detection And Identification

Detection and assessment of cracks in civil engineering structures such as roads, bridges, dams and pipelines are crucial tasks for maintaining the safety and cost-effectiveness of those concrete structures. With the recent advances in machine learning, the development of ANN- and CNN-based algorithms has become a popular approach for the automated detection and identification of concrete cracks. However, most of the proposed models are trained on images taken in ideal conditions and are only capable of achieving high accuracy when applied to the concrete images devoid of irregular illumination conditions, shadows, shading, blemishes, etc. An overview of challenges related to the automatic detection of concrete cracks in the presence of shadows is presented in this paper. In particular, difficulties associated with the application of deep learning-based methods for the classification of concrete images with shadows are demonstrated. Moreover, the limitations of the shadow removal techniques for the improvement of the crack detection accuracy are discussed.

Automatic detection of moisture damages in asphalt pavements from GPR data with deep CNN and IRS method

2020 ◽  
Vol 113 ◽  
pp. 103119 ◽  
Author(s):  
Jun Zhang ◽  
Xing Yang ◽  
Weiguang Li ◽  
Shaobo Zhang ◽  
Yunyi Jia
Keyword(s):  
Automatic Detection ◽  
Asphalt Pavements ◽  
Deep Cnn

scholarly journals Detection and Identification of Animals in Wild Life Sanctuaries using Convolutional Neural Network

2020 ◽  
Vol 8 (5) ◽  
pp. 181-185
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Automatic Extraction ◽  
Human Intervention ◽  
Wildlife Sanctuary ◽  
Time Data ◽  
Detection And Identification ◽  
Web Camera ◽  
Deep Cnn ◽  
Wild Life

Comprehensive, Precise and real time data regarding the position and characteristics of animals is necessary for safeguarding visitors inside a wildlife sanctuary. Investigations are made on the capability for automated, unambiguous and economical collection of data that are useful to perform rescue operations within the sanctuary because of the absence of other communicational sources. Web camera enables collection of photos relating to wildlife economically, conservatively as well as regularly. Extraction of information from such photos is costly, slow and requires human intervention. The proposed system demonstrates the automatic extraction of such data using Convolutional Neural Network (CNN). Deep CNN is trained for a set of images available in a wildlife dataset.

Technical Note: Deep Learning approach for automatic detection and identification of patient positioning devices for radiation therapy

2020 ◽  
Vol 47 (10) ◽  
pp. 5061-5069
Author(s):  
David H. Thomas ◽  
Leah K. Schubert ◽  
Yevgeniy Vinogradskiy ◽  
Sameer Nath ◽  
Brian Kavanagh ◽  
...  
Keyword(s):  
Radiation Therapy ◽  
Deep Learning ◽  
Patient Positioning ◽  
Automatic Detection ◽  
Technical Note ◽  
Learning Approach ◽  
Detection And Identification ◽  
Positioning Devices
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