Jun 7, 2024 · Object detection is a crucial task in computer vision that involves identifying and locating objects within an image or video. This task is fundamental for various applications, including autonomous driving, video surveillance, and medical imaging.

Jun 28, 2022 · Object Detection algorithms act as a combination of image classification and object localization. It takes an image as input and produces one or more bounding boxes with the class label attached to each bounding box.

Nov 7, 2018 · PDF | ABSRACT-This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and... | Find, read and cite all the...

We classify these methods into three main groups: anchor-based, anchor-free, and transformer-based detectors. Those approaches are distinct in the way they identify objects in the image. We discuss the insights behind these algorithms and experimental analyses to compare quality metrics, speed/accuracy tradeoffs, and training methodologies.

Nov 14, 2016 · With that overview, we are ready to return to the main goal of this post — understand image recognition using traditional computer vision techniques. An image recognition algorithm ( a.k.a an image classifier ) takes an image ( or a patch of an image ) as input and outputs what the image contains.

Nov 23, 2016 · This paper describes a machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates. This work is...

spects of object recognition. We present the architecture and main components of object recognition and discuss their role in object recognition . f varying c. e models known to the system. The information in the model database depends on the appr. ach used for the recognition. It can vary from a qualitative or functional description to pre cise .

This book discusses recent advances in object detection and recognition using deep learning methods, which have achieved great success in the field of computer vision and image processing.

Image identification makes use of techniques like detection of an object, its recognition, and segmentation. The use of artificial intelligence and machine learning enhances the rate of processing the data and maintaining the standard of the outcome. Example, by using artificial intelligence, we can very easily complete difficult tasks.

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book.