Probabilistic camera hand-off for visual surveillance

Images captured in severe atmospheric catastrophe especially in fog critically degrade the quality of an image and thereby reduces the visibility of an image which in turn affects several computer vision applications like visual surveillance detection, intelligent vehicles, remote sensing, etc. Thus acquiring clear vision is the prime requirement of any image. In the last few years, many approaches have been made towards solving this problem. In this article, a comparative analysis has been made on different existing image defogging algorithms and then a technique has been proposed for image defogging based on dark channel prior strategy. Experimental results show that the proposed method shows efficient results by significantly improving the visual effects of images in foggy weather. Also computational time of the existing techniques are much higher which has been overcame in this paper by using the proposed method. Qualitative assessment evaluation is performed on both benchmark and real time data sets for determining theefficacy of the technique used. Finally, the whole work is concluded with its relative advantages and shortcomings.

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Using a Warm Hand-Off Approach to Enroll African American Caregivers in a Multi-Site Clinical Trial: The Handshake Protocol

Journal of Applied Gerontology ◽

10.1177/0733464821992920 ◽

2021 ◽

pp. 073346482199292

Author(s):

Fayron Epps ◽

Glenna Brewster ◽

Judy S. Phillips ◽

Rachel Nash ◽

Raj C. Shah ◽

...

Keyword(s):

African American ◽

Controlled Trial ◽

Culturally Congruent ◽

Phone Calls ◽

Emory University ◽

Hand Off ◽

Site Coordinator ◽

Handshake Protocol ◽

Minority Participants ◽

African American Caregivers

“Testing Tele-Savvy” was a three-arm randomized controlled trial that recruited participants from four National Institute on Aging (NIA)–funded Alzheimer’s Disease Centers with Emory University serving as the coordinating center. The enrollment process involved each center providing a list of eligible caregivers to the coordinating center to consent. Initially, the site proposed to recruit primarily African American caregivers generated a significant amount of referrals to the coordinating center, but a gap occurred in translating them into enrolled participants. To increase the enrollment rate, a “Handshake Protocol” was established, which included a warm handoff approach. During preset phone calls each week, the research site coordinator introduced potential participants to a culturally congruent co-investigator from the coordinating center who then completed the consent process. Within the first month of implementation, the team was 97% effective in meeting its goals. This protocol is an example of a successful, innovative approach to enrolling minority participants in multi-site clinical trials.

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Interns Overestimate the Effectiveness of Their Hand-off Communication

PEDIATRICS ◽

10.1542/peds.2009-0351 ◽

2010 ◽

Vol 125 (3) ◽

pp. 491-496 ◽

Cited By ~ 80

Author(s):

V. Y. Chang ◽

V. M. Arora ◽

S. Lev-Ari ◽

M. D'Arcy ◽

B. Keysar

Keyword(s):

Hand Off

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Action Recognition Network Using Stacked Short-Term Deep Features and Bidirectional Moving Average

Applied Sciences ◽

10.3390/app11125563 ◽

2021 ◽

Vol 11 (12) ◽

pp. 5563

Author(s):

Jinsol Ha ◽

Joongchol Shin ◽

Hasil Park ◽

Joonki Paik

Keyword(s):

Action Recognition ◽

High Speed ◽

Moving Average ◽

Video Clip ◽

Visual Surveillance ◽

Temporal Information ◽

Feature Maps ◽

Short Term ◽

Accurate Analysis ◽

Difference Images

Action recognition requires the accurate analysis of action elements in the form of a video clip and a properly ordered sequence of the elements. To solve the two sub-problems, it is necessary to learn both spatio-temporal information and the temporal relationship between different action elements. Existing convolutional neural network (CNN)-based action recognition methods have focused on learning only spatial or temporal information without considering the temporal relation between action elements. In this paper, we create short-term pixel-difference images from the input video, and take the difference images as an input to a bidirectional exponential moving average sub-network to analyze the action elements and their temporal relations. The proposed method consists of: (i) generation of RGB and differential images, (ii) extraction of deep feature maps using an image classification sub-network, (iii) weight assignment to extracted feature maps using a bidirectional, exponential, moving average sub-network, and (iv) late fusion with a three-dimensional convolutional (C3D) sub-network to improve the accuracy of action recognition. Experimental results show that the proposed method achieves a higher performance level than existing baseline methods. In addition, the proposed action recognition network takes only 0.075 seconds per action class, which guarantees various high-speed or real-time applications, such as abnormal action classification, human–computer interaction, and intelligent visual surveillance.

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Watching Neurons Hand Off Molecules

Microscopy Today ◽

10.1017/s1551929500050422 ◽

2002 ◽

Vol 10 (1) ◽

pp. 3-34

Author(s):

Stephen W. Carmichael

Keyword(s):

Nerve Growth Factor ◽

Growth Factor ◽

Neurotrophic Factors ◽

Neurotrophic Factor ◽

Brain Derived Neurotrophic Factor ◽

Target Cells ◽

Nerve Growth ◽

Hand Off ◽

Presynaptic Neurons

Since the discovery of nerve growth factor, it has been thought that neurotrophic factors are released or secreted from target cells. However, more recently it has been suggested that a specific neurotrophic factor known as brain-derived neurotrophic factor (BDNF) may reach target cells directly from pre-synaptic axons. It has not been known how these molecules get from the neuron in which they are produced to the target cells. Keigo Kohara, Akihiko Kitamura, Mieko Morishima, and Tadaharu Tsumoto have demonstrated that BDNF is transported anterogradely from presynaptic neurons to target neurons.

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Hand-Off Evolution with Multiple Interfaces

IT Professional ◽

10.1109/mitp.2008.102 ◽

2008 ◽

Vol 10 (5) ◽

pp. 22-28 ◽

Cited By ~ 1

Author(s):

Ching-Lun Lin ◽

Chih-Hsiang Ho ◽

Jen-Yi Pan

Keyword(s):

Multiple Interfaces ◽

Hand Off

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