Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Associative Learning01:27

Associative Learning

2.0K
Associative learning is a fundamental concept in behavioral psychology, wherein a connection is established between two stimuli or events, leading to a learned response. This process is critical in understanding how behaviors are acquired and modified. Conditioning, the mechanism through which associations are formed, can be divided into two main types: classical conditioning and operant conditioning, each elucidating different aspects of associative learning.
Classical conditioning, also known...
2.0K
Observational Learning01:12

Observational Learning

1.4K
Albert Bandura's observational learning, also known as imitation or modeling, occurs when a person observes and imitates another's behavior. It is a quicker process than operant conditioning. A well-known example is the Bobo doll study, where children who saw an adult acting aggressively towards the doll were more likely to act aggressively when left alone, compared to those who observed a nonaggressive adult. Many psychologists view observational learning as a form of latent learning...
1.4K
Classification of Signals01:30

Classification of Signals

1.6K
In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...
1.6K
Introduction to Learning01:18

Introduction to Learning

1.6K
Learning is the process of acquiring knowledge or skills through practice or experience, leading to long-lasting behavioral changes. This acquisition occurs through interaction with the environment and requires practice or experience. For instance, mastering a skill such as surfing requires considerable practice and experience, highlighting the essential role of repeated interactions with the environment in learning.
In contrast to learned behaviors, unlearned behaviors such as crying, sexual...
1.6K
Determination of Expected Frequency01:08

Determination of Expected Frequency

2.8K
Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
2.8K
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

508
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence of...
508

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Towards the construction of a virtual yeast.

Nature·2026
Same author

Enhancing Underwater Light Field Images via Global Geometry-Aware Diffusion Process.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same author

Genomic epidemiology reveals the origins and transmission dynamics of chikungunya virus in China.

Infectious diseases of poverty·2026
Same author

QMSANet: A quaternion multi-scale attention network for robust color image denoising.

Neural networks : the official journal of the International Neural Network Society·2026
Same author

Shifting dengue virus imports into Yunnan, China, 2017-2019: epidemic lineages sparking local outbreaks.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases·2026
Same author

AI-Powered Monitoring of the Acute: Chronic Workload Ratio: Interpretable Injury Risk Prediction in Soccer Players.

Sports health·2026
Same journal

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Learning Gaze Synthesizer via 3D-eye Controlled Diffusion and Cross-domain Feature Alignment.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Underlying Semantic Diffusion for Effective and Efficient In-Context Learning.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

DiffRES: Unleashing Text-to-Image Diffusion Models for Generative Referring Expression Segmentation without Information Leakage.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

Location Matters: Frequency-Spatial Dual Space Adaptation for Cross-Domain Few-Shot Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
Same journal

BayeTopo: Bayesian-based Topology-guided Learning for Vascular Imaging Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026
See all related articles

Related Experiment Video

Updated: Apr 16, 2026

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
03:31

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

1.2K

Event oriented dictionary learning for complex event detection.

Yan Yan, Yi Yang, Deyu Meng

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |March 21, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method for complex event detection by automatically selecting meaningful concepts. This approach enhances video retrieval from large archives using semantic concept selection and dictionary learning.

    More Related Videos

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    2.1K
    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.7K

    Related Experiment Videos

    Last Updated: Apr 16, 2026

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.2K
    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception
    05:48

    Author Spotlight: Investigating the Impact of Emotional Prosodies on Voice Recognition and Perception

    Published on: August 9, 2024

    2.1K
    Rare Event Detection Using Error-corrected DNA and RNA Sequencing
    10:36

    Rare Event Detection Using Error-corrected DNA and RNA Sequencing

    Published on: August 3, 2018

    12.7K

    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Machine Learning

    Background:

    • Complex event detection aims to retrieve specific events from large video archives.
    • Current multimodal fusion schemes for event detection are well-researried.
    • Effective selection of high-level semantic concepts for event detection remains understudied.

    Purpose of the Study:

    • To propose a novel strategy for automatic selection of semantic concepts for complex event detection.
    • To introduce an event-oriented dictionary representation based on selected semantic concepts.

    Main Methods:

    • A supervised multitask lp-norm dictionary learning framework is utilized.
    • The method leverages training images of selected concepts from a semantic indexing dataset (346 concepts).
    • Concept selection is based on both event descriptions and high-level feature descriptions.

    Main Results:

    • The proposed method demonstrates efficacy in complex event detection.
    • Experimental results were validated on the TRECVID multimedia event detection dataset.

    Conclusions:

    • Automatic selection of semantic concepts significantly aids complex event detection.
    • The novel dictionary representation based on selected concepts proves effective.