End-to-end Multiplayer Violence Detection based on Deep 3D CNN

2018 ◽  
Author(s):  
Chengyang Li ◽  
Liping Zhu ◽  
Dandan Zhu ◽  
Jiale Chen ◽  
Zhanghui Pan ◽  
...  
Keyword(s):  
Violence Detection ◽  
End To End ◽  
3D Cnn

scholarly journals An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos

2020 ◽  
Vol 34 (01) ◽  
pp. 303-311 ◽  
Author(s):  
Sicheng Zhao ◽  
Yunsheng Ma ◽  
Yang Gu ◽  
Jufeng Yang ◽  
Tengfei Xing ◽  
...  
Keyword(s):  
Neural Networks ◽  
Emotion Recognition ◽  
State Of The Art ◽  
Source Code ◽  
Cross Entropy ◽  
Attention Network ◽  
Audio Features ◽  
End To End ◽  
3D Cnn ◽  
And Training

Emotion recognition in user-generated videos plays an important role in human-centered computing. Existing methods mainly employ traditional two-stage shallow pipeline, i.e. extracting visual and/or audio features and training classifiers. In this paper, we propose to recognize video emotions in an end-to-end manner based on convolutional neural networks (CNNs). Specifically, we develop a deep Visual-Audio Attention Network (VAANet), a novel architecture that integrates spatial, channel-wise, and temporal attentions into a visual 3D CNN and temporal attentions into an audio 2D CNN. Further, we design a special classification loss, i.e. polarity-consistent cross-entropy loss, based on the polarity-emotion hierarchy constraint to guide the attention generation. Extensive experiments conducted on the challenging VideoEmotion-8 and Ekman-6 datasets demonstrate that the proposed VAANet outperforms the state-of-the-art approaches for video emotion recognition. Our source code is released at: https://github.com/maysonma/VAANet.

scholarly journals Violence Detection Using Spatiotemporal Features with 3D Convolutional Neural Network

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2472 ◽  
Author(s):  
Fath U Min Ullah ◽  
Amin Ullah ◽  
Khan Muhammad ◽  
Ijaz Ul Haq ◽  
Sung Wook Baik
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Smart Cities ◽  
Automatic Monitoring ◽  
Video Stream ◽  
Surveillance Video ◽  
Softmax Classifier ◽  
Spatiotemporal Features ◽  
Violence Detection ◽  
3D Cnn

The worldwide utilization of surveillance cameras in smart cities has enabled researchers to analyze a gigantic volume of data to ensure automatic monitoring. An enhanced security system in smart cities, schools, hospitals, and other surveillance domains is mandatory for the detection of violent or abnormal activities to avoid any casualties which could cause social, economic, and ecological damages. Automatic detection of violence for quick actions is very significant and can efficiently assist the concerned departments. In this paper, we propose a triple-staged end-to-end deep learning violence detection framework. First, persons are detected in the surveillance video stream using a light-weight convolutional neural network (CNN) model to reduce and overcome the voluminous processing of useless frames. Second, a sequence of 16 frames with detected persons is passed to 3D CNN, where the spatiotemporal features of these sequences are extracted and fed to the Softmax classifier. Furthermore, we optimized the 3D CNN model using an open visual inference and neural networks optimization toolkit developed by Intel, which converts the trained model into intermediate representation and adjusts it for optimal execution at the end platform for the final prediction of violent activity. After detection of a violent activity, an alert is transmitted to the nearest police station or security department to take prompt preventive actions. We found that our proposed method outperforms the existing state-of-the-art methods for different benchmark datasets.

scholarly journals Development of 3D convolutional neural network to recognize human activities using moderate computation machine

2021 ◽  
Vol 10 (6) ◽  
pp. 3137-3146
Author(s):  
Malik A. Alsaedi ◽  
Abdulrahman Saeed Mohialdeen ◽  
Baraa Munqith Albaker
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Human Behavior ◽  
Human Activities ◽  
Smart Homes ◽  
Powerful Method ◽  
Systems Implementation ◽  
Violence Detection ◽  
Proposed Model ◽  
3D Cnn

Human activity recognition (HAR) is recently used in numerous applications including smart homes to monitor human behavior, automate homes according to human activities, entertainment, falling detection, violence detection, and people care. Vision-based recognition is the most powerful method widely used in HAR systems implementation due to its characteristics in recognizing complex human activities. This paper addresses the design of a 3D convolutional neural network (3D-CNN) model that can be used in smart homes to identify several numbers of activities. The model is trained using KTH dataset that contains activities like (walking, running, jogging, handwaving handclapping, boxing). Despite the challenges of this method due to the effectiveness of the lamination, background variation, and human body variety, the proposed model reached an accuracy of 93.33%. The model was implemented, trained and tested using moderate computation machine and the results show that the proposal was successfully capable to recognize human activities with reasonable computations.

Surgical management of extracranial carotid artery aneurysms

VASA ◽  
2016 ◽  
Vol 45 (3) ◽  
pp. 223-228 ◽  
Author(s):  
Jan Paweł Skóra ◽  
Jacek Kurcz ◽  
Krzysztof Korta ◽  
Przemysław Szyber ◽  
Tadeusz Andrzej Dorobisz ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Surgical Management ◽  
Minor Stroke ◽  
Stroke Rate ◽  
Extracranial Carotid Artery ◽  
Long Term Follow Up ◽  
End To End ◽  
Dacron Patch ◽  
Major Stroke

Abstract. Background: We present the methods and results of the surgical management of extracranial carotid artery aneurysms (ECCA). Postoperative complications including early and late neurological events were analysed. Correlation between reconstruction techniques and morphology of ECCA was assessed in this retrospective study. Patients and methods: In total, 32 reconstructions of ECCA were performed in 31 symptomatic patients with a mean age of 59.2 (range 33 - 84) years. The causes of ECCA were divided among atherosclerosis (n = 25; 78.1 %), previous carotid endarterectomy with Dacron patch (n = 4; 12.5 %), iatrogenic injury (n = 2; 6.3 %) and infection (n = 1; 3.1 %). In 23 cases, intervention consisted of carotid bypass. Aneurysmectomy with end-to-end suture was performed in 4 cases. Aneurysmal resection with patching was done in 2 cases and aneurysmorrhaphy without patching in another 2 cases. In 1 case, ligature of the internal carotid artery (ICA) was required. Results: Technical success defined as the preservation of ICA patency was achieved in 31 cases (96.9 %). There was one perioperative death due to major stroke (3.1 %). Two cases of minor stroke occurred in the 30-day observation period (6.3 %). Three patients had a transient hypoglossal nerve palsy that subsided spontaneously (9.4 %). At a mean long-term follow-up of 68 months, there were no major or minor ipsilateral strokes or surgery-related deaths reported. In all 30 surviving patients (96.9 %), long-term clinical outcomes were free from ipsilateral neurological symptoms. Conclusions: Open surgery is a relatively safe method in the therapy of ECCA. Surgical repair of ECCAs can be associated with an acceptable major stroke rate and moderate minor stroke rate. Complication-free long-term outcomes can be achieved in as many as 96.9 % of patients. Aneurysmectomy with end-to-end anastomosis or bypass surgery can be implemented during open repair of ECCA.

Reliability of the Mangled Extremity Severity Score in the Management of Peripheral Vascular Injuries in Children: A Retrospective Review

2020 ◽  
Author(s):  
Ahmed Mousa ◽  
Ossama M. Zakaria ◽  
Mai A. Elkalla ◽  
Lotfy A. Abdelsattar ◽  
Hamad Al-Game'a
Keyword(s):  
Severity Score ◽  
Vein Graft ◽  
Bypass Surgery ◽  
Age Groups ◽  
Vascular Injuries ◽  
Peripheral Vascular ◽  
Group Iii ◽  
Mangled Extremity ◽  
Group I ◽  
End To End

AbstractThis study was aimed to evaluate different management modalities for peripheral vascular trauma in children, with the aid of the Mangled Extremity Severity Score (MESS). A single-center retrospective analysis took place between 2010 and 2017 at University Hospitals, having emergencies and critical care centers. Different types of vascular repair were adopted by skillful vascular experts and highly trained pediatric surgeons. Patients were divided into three different age groups. Group I included those children between 5 and 10 years; group II involved pediatrics between 11 and 15 years; while children between 16 and 21 years participated in group III. We recruited 183 children with peripheral vascular injuries. They were 87% males and 13% females, with the mean age of 14.72 ± 04. Arteriorrhaphy was performed in 32%; end-to-end anastomosis and natural vein graft were adopted in 40.5 and 49%, respectively. On the other hand, 10.5% underwent bypass surgery. The age groups I and II are highly susceptible to penetrating trauma (p = 0.001), while patients with an extreme age (i.e., group III) are more susceptible to blunt injury (p = 0.001). The MESS has a significant correlation to both age groups I and II (p = 0.001). Vein patch angioplasty and end-to-end primary repair should be adopted as the main treatment options for the repair of extremity vascular injuries in children. Moreover, other treatment modalities, such as repair with autologous vein graft/bypass surgery, may be adopted whenever possible. They are cost-effective, reliable, and simple techniques with fewer postoperative complication, especially in poor/limited resources.

WS-Security on PRODML

2014 ◽  
Vol 1 (1) ◽  
pp. 9-34
Author(s):  
Bobby Suryajaya
Keyword(s):  
Web Services ◽  
Digital Signature ◽  
Data Transfer ◽  
Web Services Security ◽  
Soap Message ◽  
Simulation Results ◽  
End To End

SKK Migas plans to apply end-to-end security based on Web Services Security (WS-Security) for Sistem Operasi Terpadu (SOT). However, there are no prototype or simulation results that can support the plan that has already been communicated to many parties. This paper proposes an experiment that performs PRODML data transfer using WS-Security by altering the WSDL to include encryption and digital signature. The experiment utilizes SoapUI, and successfully loaded PRODML WSDL that had been altered with WSP-Policy based on X.509 to transfer a SOAP message.

Mit MindSphere die digitale Transformation vorantreiben

Controlling ◽  
2019 ◽  
Vol 31 (6) ◽  
pp. 63-65
Author(s):  
Carsten Speckmann ◽  
Péter Horváth
Keyword(s):  
Digitale Transformation ◽  
Internet Der Dinge ◽  
End To End

MindSphere ist das cloudbasierte, offene IoT-Betriebssystem von Siemens. Es verbindet Produkte, Anlagen, Systeme und Maschinen und ermöglicht es so, die Fülle von Daten aus dem Internet der Dinge (IoT) mit umfangreichen Analysen zu nutzen. Als eine sichere, skalierbare End-to-End-Lösung für die Industrie sorgt MindSphere für die Konnektivität von Anlagen und liefert somit handlungsrelevante Geschäftserkenntnisse, die zur Steigerung der Produktivität und Effizienz im gesamten Unternehmen nutzbar gemacht werden können. MindSphere ist weltweit verfügbar.

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