An AI practitioner has a database of animal photos. The AI practitioner wants to automatically identify and categorize the animals in the photos…

Object detection is a computer vision technology that deals with identifying and locating objects within an image or video. Specifically, it draws bounding boxes around detected objects (identification/localization) and assigns a class label to them (categorization). This directly addresses the requirement to automatically find where the animals are in the photos and determine what kind of animals they are. The process is automated, fulfilling the "without manual human effort" constraint once the model is trained.

1. Stanford University CS231n Course Notes. In the "Object Detection" section

it is defined as the task of classification and localization of objects. The notes state

"we want to classify each object and localize it using a bounding box."

Source: Stanford CS231n: Convolutional Neural Networks for Visual Recognition

Spring 2022

Lecture 11: Detection and Segmentation

Slides 4-6.

2. Official Vendor Documentation (Amazon Web Services). The Amazon Rekognition documentation describes its "Object and Scene Detection" feature as being able to "identify thousands of objects such as cars

furniture

or animals

and scenes such as a beach or city."

Source: AWS Documentation

Amazon Rekognition Developer Guide

"Detecting objects in images

" Section: "Objects and scenes detected in images."

3. Peer-Reviewed Academic Publication. A comprehensive survey on object detection defines the task as determining "where objects are located in a given image (object localization) and which category each object belongs to (object classification)."

Source: Zou

Z.

Shi

Z.

Guo

Y.

& Ye

J. (2019). Object Detection in 20 Years: A Survey. arXiv preprint arXiv:1905.05055

Section 1

Paragraph 1. (Note: While an arXiv preprint

this survey is widely cited and foundational in the field

reflecting academic consensus).