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Real-time Attention-Augmented Spatio-Temporal Networks for Video-based Driver Activity recognition 25

Real-time Attention-Augmented Spatio-Temporal Networks for V...

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IEEE 25th international conference on intelligent Transportation systems (ITSC)

作者： Saleh, Khaled Mihaita, Adriana-Simona Yu, Kun Chen, Fang Univ Technol Sydney Fac Engn & IT Sydney NSW Australia

ISBN: (数字)9781665468800

ISBN: (纸本)9781665468800

Identifying driver behaviour and activities from in-cabin video cameras (especially the distracting non-driving activities), has been recently shown to be effective in enhancing the safety and the driving experience in smart and partiallyautomated vehicles. In the literature, the problem of videobased driver activity recognition is often tackled by using traditional deep learning-based human-action recognition systems. Despite their powerful capabilities, they seem not well-suited for video-based driver activity recognition, due to their complex and inefficient architecture that requires a huge amount of computational resources. Additionally, given the similarities of different non-driving activities that share the same pattern of upper body movements (e.g. drinking versus eating), it makes it harder for traditional human-action recognition systems to pick up or differentiate between these subtle changes. thus, in this work we are proposing a novel framework based on an efficient spatio-temporal neural network architecture augmented with an attention mechanism that can differentiate between the subtle differences of similar non-driving activities. Our framework has been evaluated on one of the largest benchmark datasets for fine-grained recognition of driver activities and it has outperformed the state-of-art approach by more than 4% in the top-1 accuracy score with a boosting of 13x the run-time speedup during the inference.

关键词： Neural networks Computer architecture Activity recognition Benchmark testing Cameras Boosting Real-time systems

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Transfering RGB-D Models to RGB by Multi-View Embedding Space Learning for Object Detection 4

Transfering RGB-D Models to RGB by Multi-View Embedding Spac...

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4th international conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2022

作者： Liu, Jinde Zhang, Zhang University of Chinese Academy of Sciences Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665463997

In this paper, we propose a new framework for detecting objects in RGB images captured by conventional cameras by leveraging a set of labeled RGB-D data. We formulate this problem into a new multi-view learning problem, where we have the depth information in the training set that is not available in the testing set. To solve this problem, we use a three-view CCA learning method which combines visual features, depth features, and label information together to get the projection matrices. Sufficient experiments are done to demonstrate the effectiveness of our method, and improvement measures in the future are also proposed. © 2022 IEEE.

关键词： Object detection

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2023 IEEE 4th Annual Flagship India Council international Subsections conference: Computational Intelligence and Learning systems, INDISCON 2023

2023 IEEE 4th Annual Flagship India Council International Su...

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4th IEEE Annual Flagship India Council international Subsections conference, INDISCON 2023

ISBN: (纸本)9798350333558

the proceedings contain 172 papers. the topics discussed include: reconstruction optimization of economic operation of distribution network based on data mining algorithm;ROI segmentation for breast cancer classification : deep learning perspective;evaluation of hotspot performance in IoT enabled wireless sensor network using special intermediate nodes in the network;a university innovation and entrepreneurship information sharing platform based on data mining and classification algorithms;data governance based on full-service data analysis domain of power grid;minimum utilization of energy resource via MAC routing protocol for mobile sensor network;sentimental analysis of movie review based on naive bayes and random forest technique;parallel algorithm of high precision surface modeling based on differential geometry;maximization of achievable sum rate and improvement in outage probability in intelligent reflecting surface (IRS) driven NOMA networks;automated 20-20-20 timers using facial detection and facial recognition;enhancement of routing flexibility by a novel distributed approach for WSN;and improvement of reliable data transmission signal by space diversity technique in wireless communication.

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intelligent Hand Gesture recognition Using a Multichannel Surface Electromyography 6th

Intelligent Hand Gesture Recognition Using a Multichannel Su...

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6th international conference on intelligent Communication, Control and Devices, ICICCD 2024

作者： Shah, Gautam Rathor, Ajit Singh Sharma, Abhinav Attri, Rajeev Kumar Electrical Cluster SOAE UPES Uttarakhand Dehradun India Library UPES Uttarakhand Dehradun India

ISBN: (纸本)9789819783281

One of the bio-signals used to power a prosthetic hand and enhance the quality of life for amputees is myoelectric signal produced by the muscles. Furthermore, surface electromyography is the most promising technique for obtaining muscle activity;however, an effective pattern recognition system is required. this research presents a method based on EMG signals for simultaneous detection of wrist motions and hand gestures. In this method, the first signal is acquired using Myo armband with 36 intact subjects and seven hand motions have been recorded. Following signal preprocessing, ten time-domain features are retrieved, and the chosen features are then categorized using SVM, DT, RF, and XGBoost. the grid search technique is used to fine-tune the hyperparameters, and the results show which hyperparameters are optimal for the input to the classifier. Based on the experimental results, random forest was able to obtain 84.2 ± 2.7% classification accuracy. the suggested technique has been tried on a 12-generation Intel Core i5 1.30 GHz CPU equipped with 16 GB DDR4 RAM. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Formal Specification and Verification for Organization-based systems : A Survey 4

Formal Specification and Verification for Organization-based...

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4th international conference on pattern Analysis and intelligent systems, PAIS 2022

作者： Sabeg, Samra Maarouk, Toufik Messaoud El Habib Souidi, Mohammed Abbes Laghrour University of Khenchela Icosi Lab Departement of Computer Sciences Khenchela Algeria

ISBN: (数字)9781665461610

ISBN: (纸本)9781665461610

Recently, developing organizational multi-agent systems (MAS) is very difficult due to their dynamism and complexity. Consequently, checking the correctness of these MAS is a complicated task. this paper proposes a survey of the relevant works dealing with formalizing organizational models in multi-agent systems. For this purpose, we analyse the essential studies in the domain. then, we report an excellent discussion of these relevant approaches according to specific criteria. Lastly, we propose certain challenges to improve the formal specification process in organizational multi-agent systems. © 2022 IEEE.

关键词： Multi agent systems

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Two-Stage Multi-Instance Multi-Label Learning Model for Video Social Relationship recognition 4

Two-Stage Multi-Instance Multi-Label Learning Model for Vide...

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4th international conference on intelligent Computing and Human-Computer Interaction, ICHCI 2023

作者： Dong, Wenlong Ma, Zhongchen Zhu, Qing Mao, Qirong School of Computer Science and Communication Engineering Jiangsu University Zhenjiang China

ISBN: (纸本)9798350343113

Recognizing social relationships among characters from videos facilitates multimedia content analysis and helps viewers understand the storyline quickly. However, treating the information at each moment in the video equally will affect the extraction of information related to social relationships. Most existing methods only consider the social relationships between any two characters in the video, ignoring the potential correlations of social relationships among multiple characters. To address these issues, we propose a Two-Stage Multi-Instance Multi-Label learning model (TSMIML) for video social relationship recognition. In the first stage, we focus on obtaining effective social relationship features and mining which moments' information reflects the social relationships between characters better by generating multiple instances. In the second stage, we focus on discovering which social relationships exist in the video, exploring potential correlations among social relationships to promote social relationship recognition in the video. Compared with the state-of-the-Arts methods, extensive validation on the large-scale dataset has demonstrated the effectiveness of our proposed model. © 2023 IEEE.

关键词： Learning systems

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Target recognition technology for unmanned ships based on improved YOLOv5 4

Target recognition technology for unmanned ships based on im...

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2024 4th international conference on intelligent Traffic systems and Smart City, ITSSC 2024

作者： Yuan, Mingkai Liang, Bingnan Wang, Haoliang Dong, Yixuan School of Marine Engineering Dalian Maritime University Dalian116026 China Department of Automation Shanghai Jiaotong University Shanghai200240 China Dalian Key Laboratory of Swarm Control and Electrical Technology for Intelligent Ships Dalian116026 China State Key Laboratory of Maritime Technology and Safety Dalian116026 China

ISBN: (纸本)9781510686304

To enable safe and efficient autonomous navigation of unmanned ships in complex marine environments, particularly when encountering overtaking, head-on, or crossing scenarios, it is crucial to accurately identify and detect unknown unmanned vessels. this paper proposes a lightweight object detection algorithm tailored to these challenges. the lightweight network Ghostnet is used to improve the backbone network of the YOLOv5s algorithm, achieving lightweight target detection. By introducing the ECA attention mechanism, the model can better focus on important information in the image, enhancing the ability of feature representation, and improving the model's capability for complex scene understanding and target recognition and localization. Finally, the MPDIoU is used as the bounding box loss function for the YOLOv5s algorithm, which not only improves convergence speed but also obtains more accurate regression results. Comparative experiments show that the proposed improved algorithm outperforms models such as YOLOv5-BiFPN, YOLOv5-CBAM, and YOLOv5-SE in terms of model size, computational complexity, parameter count, detection speed, and average precision. © 2025 SPIE.

关键词： Marine navigation

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An intelligent Beamforming in 5G and 6G Networks Using Dual Polarization Beam Forming 4

An Intelligent Beamforming in 5G and 6G Networks Using Dual ...

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4th IEEE international conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Balassem, Zaid Ajzan Basha, C.H. Hussaian Chahal, Surjeet Malathy, V. Nandhini, P. College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq School of Engineering Sr University Department of Electrical & Electronics Engineering Warangal India Chandigarh University University Centre for Research & Development Mohali India Sr University Department of Electronics and Communication Engineering Warangal India New Prince Shri Bhavani College of Engineering and Technology Department of Mathematics Chennai India

ISBN: (纸本)9798350352931

In recent years, Beamforming of signal processing focused on wireless signals to create directional beams, signal strength, reduced interference and computational complexity in large-scale antenna arrays for addressing high data rates in specific broadcasting. And in signal transmission real-time adaptation to dynamic network for signal blockages effected with multipath connectivity in hardware and software requirements. In which, intelligent beamforming of advanced communication unlocked potential for frequencies in massive connectivity generation. therefore, this research proposes Dual Polarization Beam Forming (DPBF) to design beam patterns for 5G and 6G network which is handled using collected data. the input data is further processed into preprocessing through Kafka in order to find missing values, incorrect file formatting which are caused by file encodings and normalization. After that, feature extraction is done through Short-Term Fourier Transform (STFT) based on time-frequency analysis for detecting non-stationary wave signals in noisy environments. Finally, the design of beam pattern for polarization is done by DPBF based on desired beam shapes. the proposed DPBF achieved better results in terms of accuracy (0.959), precision (0.065), recall (0.951), F1-score (0.121) when compared with existing Extreme Gradient Boosting. © 2024 IEEE.

关键词： 5G mobile communication systems

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4th international conference on Communication and intelligent systems, ICCIS 2022

4th International Conference on Communication and Intelligen...

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4th international conference on Communication and intelligent systems, ICCIS 2022

ISBN: (纸本)9789819923212

the proceedings contain 52 papers. the special focus in this conference is on Communication and intelligent systems. the topics include: Transfer Learning-Based End-to-End Indian English recognition System;Impact of COVID-19 on the Sectors of the Indian Economy and the World;wind Farm Layout Optimization Problem Using Teaching–Learning-Based Optimization Algorithm;an Ensemble Multimodal Fusion Using Naive Bayes Approach for Haptic Identification of Objects;Chaotic Maps and DCT-based Image Steganography-cum-encryption Hybrid Approach;an Empirical Analysis and Challenging Era of Blockchain in Green Society;3D Modeling of Automated Robot for Seeding and Transplantation of Rice and Wheat Crops;metaheuristics based Task Offloading Framework in Fog Computing for Latency-sensitive Internet of things Applications;empirical Evaluation of Microservices Architecture;thermoelastic Energy Dissipation Trimming at High Temperatures in Cantilever Microbeam Sensors for IoT Applications;A Probabilistic Method to Identify HTTP/1.1 Slow Rate DoS Attacks;contactless Fingerprint Matching: A Pandemic Obligation;deep Reinforcement Learning to Solve Stochastic Vehicle Routing Problems;applying Machine Learning for American Sign Language recognition: A Brief Survey;identification of Promising Biomarkers in Cancer Diagnosis Using a Hybrid Model Combining ReliefF and Grey Wolf Optimization;prediction of Ectopic Pregnancy in Women Using Hybrid Machine Learning Techniques;Redundancy Reduction and Adaptive Bit Length Encoding-Based Purely Lossless ECG Compression;antecedents, Barriers, and Challenges of Artificial Intelligence Adoption for Supply Chains: A Tactical Review;Statistical Influence of Parameters on the Performance of SDN;Investigations on Channel Characteristics and Range Prediction of 5G mmWave (39 GHz) Wireless Communication System;cervical Spine Fracture Detection;Transmission Pricing Using MW Mile Method in Deregulated Environment;unmanned Ground Vehicle for Survey of Endangered S

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State-of-the-art digital technologies on garden landscape intelligent monitoring and topology optimization 4

State-of-the-art digital technologies on garden landscape in...

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4th international conference on Smart systems and Inventive Technology, ICSSIT 2022

作者： Zhang, Fen Zhou, Aimin Guangdong Engineering Polytechnic guangdong Guangzhou510520 China

ISBN: (纸本)9781665401180

State-of-the-art digital technologies on garden landscape intelligent monitoring and topology optimization is studied in this paper. In our algorithm, each basic image is independent, and each image is associated with its own directory. there is no need to read irrelevant directories, so that it can be compatible with other images. In this method, the object light and the reference light involved in coherent interference have the same characteristics except that the incident angle is symmetric with the normal line of the recording pattern, hence, the topology can be optimized with the referring of the related models. through the experimental research, the robustness is proven. © 2022 IEEE

关键词： Data mining

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