Crowd abnormal behavior detection based on motion similar entropy by Fei LI, Ken CHEN, Meng LI, Chunmei GUO

“…It is an important research content of graphic processing in the field of intelligent video surveillance to detect abnormal events.An algorithm based on entropy of motion similarity (EMS) to detect abnormal behavior was proposed.Based on the optical flow algorithm,taking the bottom flow block as the basic unit to get the scene motion information,according to the concept of social network model,the construction scene of the motion network model (MNM) was proposed,the division of the scene particles motion similarity was completed,and the distribution EMS of MNM was calculated in the time domain.Finally,the obtained image entropy was compared with the reasonable threshold,to determine whether abnormal behavior occured.Experimental results indicate that the proposed algo-rithm can detect abnormal behavior effectively and show promising performance while comparing with the state of the art methods.…”
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Research on SNN Learning Algorithms and Networks Based on Biological Plausibility by Bingqiang Huo, Fang Li, Siyu Peng, Hongwei Chen, Sudan Xin, Hongjun Wang

“…Spiking Neural Networks, inspired by the brain’s neuronal information processing mech- anisms, utilize sparse, event-based spike signals to emulate biological computation. …”
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The maximum residual block Kaczmarz algorithm based on feature selection by Ran-Ran Li, Hao Liu

“…We analyzed the convergence of these algorithms and demonstrated their effectiveness through numerical results, while also verifying the performance of the proposed algorithms in image reconstruction.…”
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A comprehensive survey on RGB-D-based human action recognition: algorithms, datasets, and popular applications by Yumin Zhang, Yanyong Wang

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Exploration of Algorithms and Heuristics in Puzzle Playing Activities of Early Childhood by Selvia Dwi Lusiana, Thorik Aziz

“…The findings identify several commonly used algorithmic strategies, such as edge-first, color or image-based grouping, and systematic trial and error. …”
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Analyzing cryptographic algorithm efficiency with in graph-based encryption models by Yashmin Banu, Biplab Kumar Rath, Debasis Gountia

“…In this study, we analyze the performance of RSA and ElGamal cryptographic algorithms by evaluating time and space complexity across various file types, including text, image, audio, and data of different sizes. …”
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Advanced Interpretation of Bullet-Affected Chest X-Rays Using Deep Transfer Learning by Shaheer Khan, Nirban Bhowmick, Azib Farooq, Muhammad Zahid, Sultan Shoaib, Saqlain Razzaq, Abdul Razzaq, Yasar Amin

“…Special deep learning algorithms went through a process of optimization before researchers improved their ability to detect and place objects. …”
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Variational Autoencoders-Based Algorithm for Multi-Criteria Recommendation Systems by Salam Fraihat, Qusai Shambour, Mohammed Azmi Al-Betar, Sharif Naser Makhadmeh

“…Deep learning (DL) models demonstrated outstanding performance across different domains: computer vision, natural language processing, image analysis, pattern recognition, and recommender systems. …”
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Novel Multimodal Fusion Algorithm for Non-Intrusive Anxiety Detection by Mahir Shadid, Mushfiqus Salehin Afnan, Rashed Mustafa, M. Jamshed Alam Patwary

“…Concurrently, image data from the KDEF and CK+ datasets was processed through a Convolutional Neural Network (CNN) enhanced with a Real Gabor filter, which is particularly adept at capturing textures, edges, and complex visual patterns necessary for precise image analysis and recognition. …”
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Research on intelligent video recognition method for roof water inrush signs in coal mines by Huiqing LIAN, Jia KANG, Shangxian YIN, Bin XU, Guocheng YAN, Xiangxue XIA, Baotong XU

“…In order to efficiently monitor and accurately identify water inrush signs, a self-supervised water inrush sign recognition method based on SAM-XMem is proposed based on image recognition and processing technology. This method employs pixel change rates to construct the water inrush warning system. …”
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Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm by Gao Chaomeng, Wang Yonggang

“…Firstly, a solution is proposed to solve the problem of low accuracy of general recommendation algorithm in brand goods. Collaborative filtering algorithm is used to analyze the visual communication design process of enterprise brand. …”
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Evaluation and Improvement of Generalization Performance of SAR Ship Recognition Algorithms by Chi Zhang, Xi Zhang, Jie Zhang, Gui Gao, Yongshou Dai, Genwang Liu, Yongjun Jia, Xiaochen Wang, Yi Zhang, Meng Bao

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Designing Recolorization Algorithms to Help People with Color Vision Anomalies by V. V. Sinitsyna, A. M. Prudnik

“…Researchers around are working on the task to create algorithms and software that can transform images and videos in accordance with their correct perception by people with color blindness. …”
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Desing of the algorithm, print and analysis of porous structures with modifiable parameters by Radosław Grabiec, Jacek Tarasiuk, Sebasatian Wroński

“…The basic concepts related to it were introduced and the process of creating an algorithm in Rhinoceros software was described. …”
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Robotized 3D Scanning and Alignment Method for Dimensional Qualification of Big Parts Printed by Material Extrusion by Juan Carlos Antolin-Urbaneja, Rakel Pacheco Goñi, Nerea Alberdi Olaizola, Ana Isabel Luengo Pizarro

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Tuning and Comparison of Optimization Algorithms for the Next Best View Problematic by Everardo Shain-Ruvalcaba, Efrain Lopez-Damian

“…The aim of this paper is to tune and compare different optimization algorithms on the Next Best View (NBV) problem, which consists in finding the next position that the sensor or camera needs to take to scan an object or scenery in its totality. …”
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Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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ALGORITHMIC AND PROGRAM IMPLEMENTATION OF THE PLAGIARISM DEFINITION IN LEARNING MANAGEMENT SYSTEMS by Y. B. Popova, A. V. Goloburda

“…As a result, a pairwise comparison of the documents and the formation of the image of one document relative to the N-list of the other will occur. …”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…By leveraging its advantages in image processing, deep learning technology has significantly enhanced the accuracy of plant disease and pest detection and identification. …”
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A twin CNN-based framework for optimized rice leaf disease classification with feature fusion by Prameetha Pai, S. Amutha, Mustafa Basthikodi, B. M. Ahamed Shafeeq, K. M. Chaitra, Ananth Prabhu Gurpur

“…Rice leaf images are processed to classify plants as either healthy or diseased with greater accuracy compared to conventional methods. …”
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