Comparative analysis of deep learning image detection algorithms
Abstract A computer views all kinds of visual media as an array of numerical values. As a consequence of this approach, they require image processing algorithms to inspect contents of images. This project compares 3 major image processing algorithms: Single Shot Detection (SSD), Faster Region based...
Main Authors: | Shrey Srivastava, Amit Vishvas Divekar, Chandu Anilkumar, Ishika Naik, Ved Kulkarni, V. Pattabiraman |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-05-01
|
Series: | Journal of Big Data |
Subjects: | |
Online Access: | https://doi.org/10.1186/s40537-021-00434-w |
Similar Items
-
A Smartphone-Based Application for Scale Pest Detection Using Multiple-Object Detection Methods
by: Jian-Wen Chen, et al.
Published: (2021-02-01) -
Small-Object Detection in Remote Sensing Images with End-to-End Edge-Enhanced GAN and Object Detector Network
by: Jakaria Rabbi, et al.
Published: (2020-05-01) -
Automatic Detection of Mandibular Fractures in Panoramic Radiographs Using Deep Learning
by: Dong-Min Son, et al.
Published: (2021-05-01) -
Agricultural Greenhouses Detection in High-Resolution Satellite Images Based on Convolutional Neural Networks: Comparison of Faster R-CNN, YOLO v3 and SSD
by: Min Li, et al.
Published: (2020-08-01) -
Deep Learning-Based Detection of Articulatory Features in Arabic and English Speech
by: Mohammed Algabri, et al.
Published: (2021-02-01)