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Computer technology related to computer vision and image processing
videos. Well-researched domains of object detection include face detection and pedestrian detection. Object detection has applications in many areas of
Object_detection
Object detection system
You Only Look Once (YOLO) is a series of real-time object detection systems based on convolutional neural networks. First introduced by Joseph Redmon et
You_Only_Look_Once
Machine learning algorithm
The Viola–Jones object detection framework is a machine learning object detection framework proposed in 2001 by Paul Viola and Michael Jones. It was motivated
Viola–Jones object detection framework
Viola–Jones_object_detection_framework
such as object detection, facial recognition, and multi-label classification. See (Calli et al, 2015) for a review of 33 datasets of 3D object as of 2015
List of datasets in computer vision and image processing
List_of_datasets_in_computer_vision_and_image_processing
Technique used in videos to detect moment
Moving object detection is a technique used in computer vision and image processing. Multiple consecutive frames from a video are compared by various methods
Moving_object_detection
Erroneous AI-generated content presented as true
misleading outputs by AI systems in tasks like machine translation and object detection. In 2015, hallucinations were identified in visual semantic role labeling
Hallucination (artificial intelligence)
Hallucination_(artificial_intelligence)
Computerized information extraction from images
vision include scene reconstruction, object detection, event detection, activity recognition, video tracking, object recognition, 3D pose estimation, learning
Computer_vision
Detecting small objects in digital images
Small object detection is a particular case of object detection where various techniques are employed to detect small objects in digital images and videos
Small_object_detection
Automatic analysis of video
health-care, retail, automotive, transport, home automation, flame and smoke detection, safety, and security. The algorithms can be implemented as software on
Video_content_analysis
Machine learning model family
family of machine learning models for computer vision, and specifically object detection and localization. The original goal of R-CNN was to take an input image
Region-based convolutional neural network
Region-based_convolutional_neural_network
Term in computer science
Collision detection is the computational problem of detecting an intersection of two or more objects in virtual space. More precisely, it deals with the
Collision_detection
Extraction of information from images via digital image processing techniques
analysis tasks. Real-time object detection became practical with frameworks such as YOLO (You Only Look Once), which unified detection and classification into
Image_analysis
Computer recognition of visual text
Especially important in multi-column layouts and tables. Line and word detection – Establishment of a baseline for word and character shapes, separating
Optical_character_recognition
Detection Transformer (DETR) is an object detection algorithm that applies transformers to identify and locate objects in images. It was introduced in
Detection_Transformer
Topical guide to object recognition
impossible to represent all appearances of an object. Uses edge detection techniques, such as the Canny edge detection, to find edges. Changes in lighting and
Outline_of_object_recognition
Type of database that uses vectors to represent other data
search, semantic search, multi-modal search, recommendations engines, object detection, and retrieval-augmented generation (RAG). Vector embeddings are mathematical
Vector_database
Method of 3D reconstruction from moving objects
Kybernetika. 46 (5): 926–937. Viola, P.; Jones, M. (2001). "Rapid object detection using a boosted cascade of simple features". Proceedings of the 2001
Structure_from_motion
Machine learning method to transfer knowledge from a large model to a smaller one
successfully used in several applications of machine learning such as object detection, acoustic models, medical imaging and natural language processing.
Knowledge_distillation
Process used in video coding/compression
a scene is reconstructed using images from a moving camera. Moving object detection Graphics processing unit Vision processing unit Scale-invariant feature
Motion_estimation
Shootdown of unidentified object
On February 11, 2023, an octagonal unidentified flying object was detected over northern Montana. It disappeared until it was spotted the next day in Wisconsin
2023 Lake Huron high-altitude object
2023_Lake_Huron_high-altitude_object
Process supporting machine learning
image classification, object detection, semantic segmentation, instance segmentation, and keypoint labelling.. Object detection tasks typically involve drawing
Data_annotation
Being seen by someone or something
police discovering information about crimes". Detection dog Object detection Signal detection theory "detection; noun". Cambridge University Dictionary. Retrieved
Detection
Content-based image retrieval
query object. The Pailitao application uses a deep CNN model with branches for joint detection and feature learning to discover the detection mask and
Reverse_image_search
Method of spatial measurement using laser
light detection and ranging or laser imaging, detection, and ranging, often stylized LiDAR) is a method for determining ranges by targeting an object or
Lidar
Open source AI framework by Google
This initial release included only five pipelines examples: Object Detection, Face Detection, Hand Tracking, Multi-hand Tracking, and Hair Segmentation
MediaPipe
3D reconstruction technique
conditions. These performed best when limited to orbiting around individual objects, such as a drum set, plants or small toys. Since the original paper in
Neural_radiance_field
Intellectual property provider
signed first license deal in March 2018. In 2018, Chips&Media added object detection IP to its product line up. WAVE is multi-standard encoder and decoder
Chips&Media
Feature descriptor used in computer vision
descriptor used in computer vision and image processing for the purpose of object detection. The technique counts occurrences of gradient orientation in localized
Histogram of oriented gradients
Histogram_of_oriented_gradients
Computational navigational technique used by robots and autonomous vehicles
beam) or 2D- (sweeping) laser rangefinders, 3D high definition light detection and ranging (lidar), 3D flash lidar, 2D or 3D sonar sensors, and one or
Simultaneous localization and mapping
Simultaneous_localization_and_mapping
Concept in computer vision
processing like morphology etc.) object localisation is required which may make use of this technique. Foreground detection separates foreground from background
Foreground_detection
Family of computer vision models
in various computer vision tasks, including image classification, object detection, and segmentation. EfficientNet introduces compound scaling, which
EfficientNet
Chinese artificial intelligence company
develops technologies including facial recognition, image recognition, object detection, optical character recognition, medical image analysis, video analysis
SenseTime
American computer scientist
the suggestion that entrants be required to indicate where in an image an object appeared rather than only whether it was present; Li invited him to join
Alexander_Berg
Analyzing AI systems by removing parts
used to test systems that perform tasks such as speech recognition, object detection, and robot control. The term is credited to Allen Newell, one of the
Ablation (artificial intelligence)
Ablation_(artificial_intelligence)
Approach used in computer vision systems
stitching, 3D reconstruction and object recognition. Corner detection overlaps with the topic of interest point detection. A corner can be defined as the
Corner_detection
Family of computer vision models designed for efficient inference on mobile devices
neural network (CNN) architectures designed for image classification, object detection, and other computer vision tasks. They are designed for small size
MobileNet
Algorithm in computer image processing
In computer science, landmark detection is the process of finding significant landmarks in an image. This originally referred to finding landmarks for
Landmark_detection
Family of machine learning techniques
convergence than uniform sampling. Hard negative mining originated in object detection in the 1990s, where it was referred to as bootstrapping (not to be
Hard_negative_mining
Vehicle operated with reduced or no human input on public roads
identify objects and their trajectories. Some systems use Bayesian simultaneous localization and mapping (SLAM) algorithms. Another technique is detection and
Self-driving_car
Particular task in computer vision
to object recognition and/or object tracking. In other domains, such as histogram analysis, blob descriptors can also be used for peak detection with
Blob_detection
American computer scientist
neural networks for object detection. The authors reported substantial improvements over previous results on the PASCAL VOC object-detection benchmark. Darrell
Trevor_Darrell
Ensemble learning method
specific category of object. The idea is closely related with recognition, identification, and detection. Appearance based object categorization typically
Boosting_(machine_learning)
Chinese-Canadian scientist
PMC 8888633. PMID 35232991. https://encord.com/blog/yolo-object-detection-guide/ YOLO Object Detection Guide Website Archived 11 April 2022 at the Wayback
Alexander_Wong_(scientist)
Type of artificial neural network
networks. Simplified example of training a feedforward neural network in object detection: The network is trained by multiple images known to depict starfish
Feedforward_neural_network
Locating a moving object by analyzing frames of a video
similarity measure (Bhattacharyya coefficient). Contour tracking: detection of object boundary (e.g. active contours or Condensation algorithm). Contour
Video_tracking
Piece of information about the content of an image
such as points, edges or objects. Features may also be the result of a general neighborhood operation or feature detection applied to the image. Other
Feature_(computer_vision)
Image-based positioning and orientation of a robot
image processing techniques for lens distortion removal, etc. Feature detection: define interest operators, and match features across frames and construct
Visual_odometry
Image and video management software
on a device with the server. Immich includes an automatic face and object detection algorithm for tagging photos and a memories feature, surfacing past
Immich
Digital image features for object recognition
to a detection window that acts like a bounding box to the target object (the face in this case). In the detection phase of the Viola–Jones object detection
Haar-like_feature
Object detection system using radio waves
towards the radar receiver are the desirable ones that make radar detection work. If the object is moving either toward or away from the transmitter, there
Radar
Type of data structure algorithm
name "integral image" and prominently used within the Viola–Jones object detection framework in 2001. Historically, this principle is very well known
Summed-area_table
Open source deep learning library
tasks including image classification, object detection, semantic segmentation, instance segmentation, keypoint detection, and multi-target workflows. Albumentations
Albumentations
Store that does not contain a checkout
object detection, multitarget tracking, and pose estimation. Object detection is the process of identifying objects within an image. Object detection
Cashierless_store
Process which assigns captioning to a digital image
existence. Content-based image retrieval Object categorization from image search Object detection Outline of object recognition Barrat, Sabine; Tabbone, Salvatore
Automatic_image_annotation
Technique in machine learning
Intent detection Sentiment analysis Machine translation Speech recognition Language model pre-training Image recognition: Facial recognition Object detection
Curriculum_learning
American space and aeronautics agency
1990s NASA has run many NEO detection programs from Earth bases observatories, greatly increasing the number of objects that have been detected. Many
NASA
Type of imaging sensor
event-driven deep convolutional neural networks. Segmentation and detection of moving objects viewed by an event camera can seem to be a trivial task, as it
Event_camera
Type of diagnosis assisted by computers
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images
Computer-aided_diagnosis
what is currently available for object detection. It is not within the scope of VIRAT to fund research in object detection, unless it is somehow related
VIRAT
Computer graphics process
reconstruction is the process of capturing the shape and appearance of real objects along a temporal dimension. In other words, it adds the concept of time
4D_reconstruction
Algorithmic processing of digitally-represented images
database. Object detection and Recognition: Identifying and recognising objects within images, especially in complex scenarios with multiple objects and occlusions
Digital_image_processing
Australian company headquartered in Port Melbourne, that produces automated object detection services for video from aircraft and surface sensors used for intelligence
Sentient_Vision_Systems
Topics referred to by the same term
electronic system Model organism database, a biological database Moving object detection, a computing technology related to image processing Multiple organ
Mod
American computer vision researcher
recognition and machine learning. He is the co-inventor of the Viola–Jones object detection framework along with Michael Jones. He won the Marr Prize in 2003 and
Paul_Viola
Problem in computer vision and robotics
to have a robot with sensors and cameras attached to it pick-up known objects with random poses out of a bin using a suction gripper, parallel gripper
Bin_picking
Series of convolutional neural networks for image classification
image classification, as the network in the Fast Region-based CNN for object detection, and as a base network in neural style transfer. The series was historically
VGGNet
First commercially available robotic vacuum cleaner
within 1" of objects without colliding with them. This object detection is fairly reliable, but sometimes fails if the robot approaches an object with a sharp
Electrolux_Trilobite
Digitalisation of analog documents
labor. The problems addressed are related to semantic segmentation, object detection, optical character recognition (OCR), handwritten text recognition
Document_processing
Type of image
saliency maps that accurately estimate all the salient image details. Object detection and recognition: Instead of applying a computationally complex algorithm
Saliency_map
Sub-area of digital image processing
particular, GP has been used for developing accurate classifiers for object detection, classification of medical images, and optical character recognition
Evolutionary_image_processing
Technology capable of matching a face from an image against a database of faces
contains other objects gained traction in the early 1990s with the principal component analysis (PCA). The PCA method of face detection is also known as
Facial_recognition_system
Deep neural network for image classification, released 2016
Small, Low Power Fully Convolutional Neural Networks for Real-Time Object Detection for Autonomous Driving". arXiv:1612.01051 [cs.CV]. Nunes Fernandes
SqueezeNet
Extraction of 3D data from digital images
3D information can be extracted by examining the relative positions of objects in the two panels. This is similar to the biological process of stereopsis
Computer_stereo_vision
Video motion analysis is a technique used to get information about moving objects from video. Examples of this include gait analysis, sport replays, speed
Video_motion_analysis
cables to a land-based processing center. To enable long range target detection (far away from the shore), one can use a powerful mobile projector, deployable
Bistatic_sonar
Series of Iranian humanoid robots
robot has the abilities of face detection and counting, object detection and position measurement, activity detection, speech recognition (speech to text)
Surena_(robot)
Multistage statistical classification scheme
is most commonly used in image processing for object detection and tracking, primarily facial detection and recognition. The first cascading classifier
Cascading_classifiers
Astronomical object not gravitationally bound to a star
colleagues, following the detection of ʻOumuamua, predicts that "The steady-state population of similar, ~100 m scale interstellar objects inside the orbit of
Interstellar_object
Process of recording the movement of objects or people
mo-cap, for short) is the process of recording high-resolution movement of objects or people into a computer system. It is used in military, entertainment
Motion_capture
Image segmentation in computer vision
counterpart responsible for the object detection task. Conversely, the Markov network responsible for detection builds the object proposal graph with inputs
Object_co-segmentation
Object Detection with ML.NET". September 20, 2020. "GitHub - microsoft/VoTT: Visual Object Tagging Tool: An electron app for building end to end Object Detection
List of manual image annotation tools
List_of_manual_image_annotation_tools
Feature detection algorithm in computer vision
in the Scholarpedia article on SIFT. The detection and description of local image features can help in object recognition. The SIFT features are local
Scale-invariant feature transform
Scale-invariant_feature_transform
Identification of human faces in images
faces in a visual scene. Face detection can be regarded as a specific case of object-class detection. In object-class detection, the task is to find the locations
Face_detection
Geometric entity created by a 3D reconstruction technique
technique introduced by A. Laurentini. This technique assumes the foreground object in an image can be separated from the background. Under this assumption
Visual_hull
American technology company
Velodyne’s sensors have a range of up to 300 meters and can be used for object detection without requiring additional sensor fusion. When mounted on a moving
Velodyne_Lidar
Preco Electronics Inc is a multinational vendor of radar-based object detection systems headquartered in Boise, Idaho, United States. Preco was founded
Preco
Soviet nonacoustic submarine detection system
Система обнаружения кильватерного следа, "wake object detection system"), is a non acoustic submarine detection system created by the Soviet Union. SOKS functions
SOKS
Open-source image processing web service
and supports smart image cropping using facial recognition and other object detection algorithms. Thumbor is free software licensed under the MIT License
Thumbor
Computer technology
Pedestrian detection is an essential and significant task in any intelligent video surveillance system, as it provides the fundamental information for
Pedestrian_detection
Topics referred to by the same term
gradients, used in computer vision and image processing for the purpose of object detection House of Guitars Arkansas Razorbacks, the sports teams of the University
Hog
Overview of artificial intelligence for surveillance
from video surveillance cameras in order to recognize humans, vehicles, objects, attributes, and events. Security contractors program the software to define
Artificial intelligence for video surveillance
Artificial_intelligence_for_video_surveillance
Optical character recognition technology
deployed on the A1 road and at the Dartford Tunnel. The first arrest through detection of a stolen car was made in 1981. However, ANPR did not become widely
Automatic number-plate recognition
Automatic_number-plate_recognition
Approach to create a short video summary of a long video
analyzes moving objects (also called events) in a database of objects and activities. The final output is a new, short video clip in which objects and activities
Video_synopsis
Tasks in machine learning
incremental learning. Simplified example of training a neural network in object detection: The network is trained by multiple images known to depict starfish
Training, validation, and test data sets
Training,_validation,_and_test_data_sets
Machine learning technique
attention helps models focus on relevant image regions, enhancing object detection and image captioning. From the original paper on vision transformers
Attention_(machine_learning)
Method for Background Subtraction". Background Modeling and Foreground Detection for Video Surveillance. pp. 7.1 – 7.23. doi:10.1201/b17223-10. ISBN 978-1-4822-0537-4
ViBe
Computational model used in machine learning
large datasets. Simplified example of training a neural network in object detection: The network is trained by multiple images known to depict starfish
Neural network (machine learning)
Neural_network_(machine_learning)
Machine learning model for vision processing
preprocessor. The Swin Transformer achieved state-of-the-art results on some object detection datasets such as COCO, by using convolution-like sliding windows of
Vision_transformer
More advanced image processing techniques must be applied to recover the object. The objective of image restoration techniques is to reduce noise and recover
Image restoration by artificial intelligence
Image_restoration_by_artificial_intelligence
Type of intrusion detection system
A host-based intrusion detection system (HIDS) is an intrusion detection system that is capable of monitoring and analyzing the internals of a computing
Host-based intrusion detection system
Host-based_intrusion_detection_system
travel, tourism, insurance
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
OBJECT DETECTION
travel, tourism, insurance