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An ensemble based approach for violence detection in videos using deep transfer learning

Multimedia Tools and Applications 2025年第12期84卷 11001-11025页

作者： Kaur, Gurmeet Singh, Sarbjeet Department of Computer Science and Engineering UIET Panjab University Chandigarh India

The detection of violence in videos has become an extremely valuable application in real-life situations, which aim to maintain and protect people’s safety. Despite the complexities inherent in videos and the abrupt nature of violent actions, the field has seen several approaches, yet achieving consistent performance remains elusive, especially with advanced real-life datasets. Presenting a solution, the paper proposes a Bagging ensemble based approach comprising three pretrained models integrated with stacked Long Short-Term Memory (LSTM) to enhance individual model performance. This ensemble approach is rigorously analyzed on two publicly accessible datasets, RLVS and RWF-2000, providing remarkable accuracy (96.6%, 92.7%) and F1-scores (96.6%, 93.0%). Additionally, a cross-dataset analysis demonstrates the model’s ability to generalize across diverse datasets. Furthermore, a study of ablation highlighting the efficacy and optimal selection of components in augmenting the proposed ensemble’s efficiency. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Long short-term memory

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Projection-algebras and Quantum Logic

Journal of Applied Logics

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Journal of Applied Logics 2024年第4期11卷 463-498页

作者： Lehmann, Daniel Selim and Rachel Benin School of Computer Science and Engineering and Quantum Information Science Center Hebrew University Jerusalem91904 Israel

P-algebras are a non-commutative, non-associative generalization of Boolean algebras that are for quantum logic what Boolean algebras are for classical logic. P-algebras have type ⟨X, 0,′, ·⟩ where 0 is a constant,′ is unary and · is binary. Elements of X are called features. A partial order is defined on the set X of features by x ≤ y iff x · y = x. Features commute, i.e., x · y = y · x iff x · y ≤ x. Features x and y are said to be orthogonal iff x · y = 0 and orthogonality is a symmetric relation. The operation + is defined as the dual of · and it is commutative on orthogonal features. The closed subspaces of a separable Hilbert space form a P-algebra under orthogonal complementation and projection of a subspace onto another one. P-algebras are complemented orthomodular posets but they are not lattices. Existence of least upper bounds for ascending sequences is equivalent to the existence of least upper bounds for countable sets of pairwise orthogonal elements. Atomic algebras are defined and their main properties are studied. The logic of P-algebras is then completely characterized. The language contains a unary connective corresponding to the operation′ and a binary connective corresponding to the operation "·". It is a substructural logic of sequents where the Exchange rule is extremely limited. It is proved to be sound and complete for P-algebras. © 2024, College Publications. All rights reserved.

关键词： Hilbert spaces

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Continuously non-malleable codes from block ciphers in split-state model

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Cybersecurity 2024年第2期7卷 68-80页

作者： Anit Kumar Ghosal Dipanwita Roychowdhury Department of Computer Science and Engineering I KharagpurKharagpurWest BengalIndia

Non-malleable code is an encoding scheme that is useful in situations where traditional error correction or detection is impossible to *** ensures with high probability that decoded message is either completely unrelated or the original one,when tampering has no ***,standard version of non-malleable codes provide security against one time tampering *** ciphers are successfully employed in the construction of non-malleable *** construction fails to provide security when an adversary tampers the codeword more than *** non-malleable codes further allow an attacker to tamper the message for polynomial number of *** this work,we propose continuous version of non-malleable codes from block ciphers in split-state *** construction provides security against polynomial number of tampering attacks and it preserves *** the tam-pering experiment triggers self-destruct,the security of continuously non-malleable code reduces to security of the underlying leakage resilient storage.

关键词： Block cipher Non-malleable code Split-state model Tamper-resilient cryptography

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Enhanced Object Detection and Classification via Multi-Method Fusion

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computers, Materials & Continua 2024年第5期79卷 3315-3331页

作者： Muhammad Waqas Ahmed Nouf Abdullah Almujally Abdulwahab Alazeb Asaad Algarni Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Computer Sciences Faculty of Computing and Information TechnologyNorthern Border UniversityRafha91911Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-siGyeonggi-do15073South Korea

Advances in machine vision systems have revolutionized applications such as autonomous driving,robotic navigation,and augmented *** substantial progress,challenges persist,including dynamic backgrounds,occlusion,and limited labeled *** address these challenges,we introduce a comprehensive methodology toenhance image classification and object detection *** proposed approach involves the integration ofmultiple methods in a complementary *** process commences with the application of Gaussian filters tomitigate the impact of noise *** images are then processed for segmentation using Fuzzy C-Meanssegmentation in parallel with saliency mapping techniques to find the most prominent *** Binary RobustIndependent Elementary Features(BRIEF)characteristics are then extracted fromdata derived fromsaliency mapsand segmented *** precise object separation,Oriented FAST and Rotated BRIEF(ORB)algorithms *** Algorithms(GAs)are used to optimize Random Forest classifier parameters which lead toimproved *** method stands out due to its comprehensive approach,adeptly addressing challengessuch as changing backdrops,occlusion,and limited labeled data concurrently.A significant enhancement hasbeen achieved by integrating Genetic Algorithms(GAs)to precisely optimize *** minor adjustmentnot only boosts the uniqueness of our system but also amplifies its overall *** proposed methodologyhas demonstrated notable classification accuracies of 90.9%and 89.0%on the challenging Corel-1k and MSRCdatasets,***,detection accuracies of 87.2%and 86.6%have been *** ourmethod performed well in both datasets it may face difficulties in real-world data especially where datasets havehighly complex *** these limitations,GAintegration for parameter optimization shows a notablestrength in enhancing the overall adaptability and performance of our system.

关键词： BRIEF features saliency map fuzzy c-means object detection object recognition

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Improving social interaction of the visually impaired individuals through conversational assistive technology

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International Journal of Intelligent Computing and Cybernetics 2024年第1期17卷 126-142页

作者： Komal Ghafoor Tauqir Ahmad Muhammad Aslam Samyan Wahla Department of Computer Science University of Engineering and TechnologyLahorePakistan

Purpose:Assistive technology has been developed to assist the visually impaired individuals in their social *** designed to enhance communication skills,facilitate social engagement and improve the overall quality of life,conversational assistive technologies include speech recognition APIs,text-to-speech APIs and various communication tools that are *** real-time *** natural language processing(NLP)and machine learning algorithms,the technology analyzes spoken language and provides appropriate responses,offering an immersive experience through voice commands,audio feedback and vibration ***/methodology/approach:These technologies have demonstrated their ability to promote self-confidence and self-reliance in visually impaired individuals during social ***,they promise to improve social competence and foster better *** short,assistive technology in conversation stands as a promising tool that empowers the visually impaired individuals,elevating the quality of their social ***:The main benefit of assistive communication technology is that it will help visually impaired people overcome communication barriers in social *** technology helps them communicate effectively with acquaintances,family,co-workers and even strangers in public *** enabling smoother and more natural communication,it works to reduce feelings of isolation and increase overall quality of ***/value:Research findings include successful activity recognition,aligning with activities on which the VGG-16 model was trained,such as hugging,shaking hands,talking,walking,waving and *** originality of this study lies in its approach to address the challenges faced by the visually impaired individuals in their social interactions through modern *** adds to the body of knowledge in the area of assistive technologies,which contribute to the empowerment and social in

关键词： Dataset(DS) Visually impaired person(VIP’S) Natural language processing(NLP) Human activity recognition(HAR)etc

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HandRT: Simultaneous Hand Shape and Appearance Reconstruction with Pose Tracking from Monocular RGB-D Video

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IEEE Transactions on Pattern Analysis and Machine Intelligence 2025年第7期47卷 5625-5635页

作者： Kalshetti, Pratik Chaudhuri, Parag Indian Institute of Technology Bombay Department of Computer Science and Engineering India

We propose a method to reconstruct a personalized hand avatar, representing the user's hand shape and appearance, from a monocular RGB-D video of a hand performing unknown hand poses under unknown illumination. Our method, HandRT, jointly optimizes hand pose, shape, appearance, and lighting parameters using a physically-based shading model in a differentiable rendering framework incorporating Monte Carlo path tracing. HandRT extends our previous work, Intrinsic Hand Avatar, by relaxing the assumption of a known coarse hand pose and utilizing depth data in the optimization. Specifically, we introduce an articulated registration energy based on iterative closest point over the depth point cloud that enables reconstruction from unknown hand poses via tracking across frames. Thus, we can reconstruct the avatar from arbitrary poses with high accuracy without relying on an off-the-shelf 2D joint detector at each frame. Further, HandRT is capable of precisely tracking the reconstructed avatar from either RGB or RGB-D input. Our evaluation demonstrates that our method outperforms existing hand avatar reconstruction methods on all commonly used metrics while producing significantly accurate mesh compared to state-of-the-art hand mesh recovery methods by a large margin on public and our captured datasets. To facilitate future research, we release our code at https://***/pmkalshetti/handrt © 1979-2012 IEEE.

关键词： Mesh generation

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Early-stage stroke prediction based on Parkinson and wrinkles using deep learning

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Neural Computing and Applications 2024年第30期36卷 18781-18805页

作者： Haritha, T. Babu, A. V. Santhosh Department of Information Technology Vivekanandha College of Engineering for Women Tamilnadu Tiruchengode India Department of Computer Science and Engineering Vivekanandha College of Engineering for Women Tamilnadu Tiruchengode India

The application of noninvasive methods to enhance healthcare systems has been facilitated by the development of new technology. Among the four major cardiovascular diseases, stroke is one of the deadliest and potentially fatal, but, if detected early enough, a patient's life may be spared. Most stroke research has centered on MRI and CT scans for uncomplicated categorization. This medical approach (imaging) is costly, time-consuming and needs the utilization of complex technology. To make up for these shortcomings, however, there has been a lot of interest in adopting noninvasive, measurable EEGs. Nevertheless, the raw data should be classified before the proper characteristics can be formed, both the forecasting algorithms and the analytical techniques demand time. As a result, this work proposes a deep learning-based model that aims to predict the chance of stroke at an early stage utilizing Parkinson's disease and wrinkles as markers. A patient may have a stroke disease if they are diagnosed with both Parkinson's disease and wrinkles. To the best of our knowledge, this research is the first to use these biomarkers to predict the risk of having a stroke. The proposed model achieves a higher accuracy of 94.7% on the considered dataset. Additionally, the recommended model was evaluated and tested in terms of loss, training time, accuracy, recall, and F1-score versus the other existing models. With less price and pain than present testing approaches, these discoveries are predicted to result in major enhancements in the early detection of strokes. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Forecasting

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Multiview data fusion technique for missing value imputation in multisensory air pollution dataset

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Journal of Ambient Intelligence and Humanized Computing 2024年第8期15卷 3173-3191页

作者： Middya, Asif Iqbal Roy, Sarbani Department of Computer Science and Engineering Jadavpur University Kolkata India

The missing readings in various sensors of air pollution monitoring stations is a common issue. Those missing sensor readings may greatly influence the performance of monitoring and analysis of air pollution data. To address this problem, in this paper, a multi-view based missing value (MV) imputation method called MVDI (Multi-View Data Imputation) is proposed for air pollution related time series data. MVDI combines four models namely LSTM (Long-Short Term Memory), IDS (Inverse Distance Squared), SVR (Support Vector Regressor), and KNN (K-Nearest Neighbors) to estimate MVs. These four models are mainly employed to capture the variations in data from different views of the dataset. Here, different views represent different portions (subsets) of the actual dataset. The estimates of MVs from all the views are combined using a kernel function to get an overall result. The proposed model MVDI is evaluated on real-world air pollution dataset in terms of RMSE, MAE, MAPE, and R2. The experimental results show that MVDI dominates over the baseline methods namely AR (AutoRegressive), ARIMA (AutoRegressive Integrated Moving Average), RFR (Random Forest Regressor), ANN (Artificial Neural Network), LI (Linear Interpolation), NN (Nearest Neighbors), MI (Mean Imputation), CNN (Convolutional Neural Network), ConvLSTM (Convolutional LSTM). © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Time series

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Socially Aware V2X Localized QoS

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IEEE Internet of Things Journal 2024年第15期11卷 25925-25938页

作者： Kaliski, Rafael Han, Yue-Hua National Sun Yat-sen University Department of Computer Science and Engineering Kaohsiung804 Taiwan Academia Sinica Research Center for Information Technology Innovation Taipei115 Taiwan National Taiwan University of Science and Technology Department of Computer Science and Information Engineering Taipei106 Taiwan

Vehicle to Everything (V2X) is a core 5G technology. V2X and its enabler, Device-to-Device (D2D), are essential for the Internet of Things (IoT) and the Internet of Vehicles (IoV). V2X enables vehicles to communicate with other vehicles (V2V), networks (V2N), and infrastructure (V2I). While V2X enables ubiquitous vehicular connectivity, the impact of bursty data on the network's overall Quality of Service (QoS), such as when a vehicle accident occurs, is often ignored. In this work, we study both 4G and 5G V2X utilizing Evolved Universal Terrestrial Radio Access New Radio (E-UTRA-NR) and propose the use of socially aware 5G NR dual connectivity (en-DC) for traffic differentiation. We also propose localized QoS, wherein high-priority QoS flows traverse 5G road side units (RSUs) and normal-priority QoS flows traverse 4G base station (BS). We formulate a max-min fair QoS-aware nonorthogonal multiple access (NOMA) resource allocation scheme, QoS reclassify. QoS reclassify enables localized QoS and traffic steering to mitigate bursty network traffic's impact on the network's overall QoS. We then solve QoS reclassify via integer linear programming (ILP) and derive its approximation. We demonstrate that both optimal and approximation QoS reclassify resource allocation schemes in our socially aware QoS management methodology outperform socially unaware legacy 4G V2X algorithms (no localized QoS support, no traffic steering) and socially aware 5G V2X (no localized QoS support, yet utilizes traffic steering). Our proposed QoS reclassify scheme's QoS flow end-to-end latency requires only approx 15% of the time legacy 4G V2X requires. © 2014 IEEE.

关键词： Quality of service

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Feature engineering in learning-to-rank for community question answering task

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International Journal of computers and Applications 2024年第8期46卷 555-566页

作者： Sajid, Nafis Hasan, Md. Rashidul Ibrahim, Muhammad Department of Computer Science and Engineering University of Dhaka Dhaka Bangladesh

Community question answering (CQA) forums are Internet-based platforms where users ask questions about a topic and other expert users try to provide solutions. Many CQA forums such as Quora, Stackoverflow, Yahoo!Answer, StackExchange exist with a lot of user-generated data. These data are leveraged in automated CQA ranking systems where similar questions (and answers) are presented in response to the user's query. In this work, we empirically investigate a few aspects of this domain. First, in addition to traditional features like Term Frequency (TF), Inverse Document Frequency (IDF), Best Match 25 (BM25), etc., we introduce a Bidirectional Encoder Representations from Transformers (BERT)-based feature that captures the semantic similarity between the question and answer. Second, most of the existing research works have focus on features extracted only from the question part;features extracted from answers have not been explored extensively. We combine both types of features in a linear fashion. Third, using our proposed concepts, we conduct an empirical investigation with different rank-learning algorithms, some of which have not been used so far in CQA domain. On three standard CQA datasets, our proposed framework achieves state-of-the-art performance (0.56, 0.58 and 0.60 NDCG@10 values). We also analyze the importance of the features we use in our investigation. This work is expected to guide the practitioners to devise a better set of features for the CQA retrieval task. © 2024 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Semantics

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