… image understanding object detection will be more prevalent. In the future, we will be able
to implement object detection in much more mundane workings of our life. Our review paper …

… models explored in [11] and object detection models like R-… a review of different state-of-the-art
object detection models … models in Sect. 2 with some contextual subsections. In Sect. …

… in image classification, segmentation and object detection. Recent advances of deep …
review of various deep architectures and model highlighting characteristics of particular model…

… , a significant improvement in the performance of object detection models has been …
This review paper starts with a quick overview of object detection followed by object detection …

… deep models are … and object detection but pays little attention on detailing specific algorithms.
Different from it, our work not only reviews deep learning-based object detection models …

… datasets used for testing or training the object detection model. This paper made a systematic
classification and summary in the object detection field, which can be meaningful and …

… 2019 Review on deep learning object detection models This work contains a detailed
analysis of object detection models available till 2019 by using Microsoft COCO dataset [22]. …

… The goal of object detection is to develop computational models and techniques that provide
one of the most basic pieces of knowledge needed by computer vision applications: What …

… ), now we discuss models for object recognition and Keras TensorFlow; … models are classified
based detectors in the region (Faster R-CNN, R-FCN, FPN) and single shot detectors (SSD …

Object detection is widely used in the field of computer vision … During the development of
half a century, object detection … At present, the approach of object detection has been largely …