Expectation-Maximization Aided Modified Weighted Sequential Energy Detector for Distributed Cooperative Spectrum Sensing by Mohammed Rashid, Jeffrey A. Nanzer

“…The estimated states are then used in mWSED to compute its test statistics, and the algorithm is referred to here as the EM-mWSED algorithm. …”
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Sequential Inversion for Helicopter Time-Domain Electromagnetics Based on a Regularized Extended Kalman Filtering by Sirui Zhou, Jun Lin, Chuandong Jiang, Haigen Zhou, Yanzhang Wang

“…We also introduce a vertical roughness regularization term to avoid overfitting issues during the inversion process. Based on the sequential processing strategy of measuring while inverting, the REKF algorithm yields the optimal solution of the inversion objective function in just a few iterations, or even a single iteration, enabling near real-time calculations. …”
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Emotion recognition with a Randomized CNN-multihead-attention hybrid model optimized by evolutionary intelligence algorithm by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Filippo Sanfilippo

“…Emotion recognition systems are vital for various applications, yet existing models often face limitations in computational efficiency and accuracy, especially when handling complex emotional expressions in sequential data. To address these challenges, we propose an innovative emotion recognition framework that integrates a Randomised Convolutional Neural Network (RCNN) with a Multi-Head Attention model, further optimized by the Football Team Training Algorithm (FTTA) metaheuristic to enhance network parameters effectively. …”
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A Two-Stage Sequential Framework for Traffic Accident Post-Impact Prediction Utilizing Real-Time Traffic, Weather, and Accident Data by Amirhossein Abdi, Seyedehsan Seyedabrishami, Steve O’Hern

“…Detecting road accident impacts as promptly as possible is essential for intelligent traffic management systems. …”
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Sequential Hybrid Integration of U-Net and Fully Convolutional Networks with Mask R-CNN for Enhanced Building Boundary Segmentation from Satellite Imagery by Rojgar Qarani Ismael, Haval Abduljabbar Sadeq

“… In the recent years, building boundary segmentation obtained significant advancement through using deep learning. The present algorithms, such as Convolutional Neural Network (CNN) are unable to detect buildings in challenging urban areas like occlusions. …”
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Particle filtering based semi-blind estimation for MIMO-OFDM time-varying channel by JING Yuan, YIN Fu-liang, ZENG Shuo

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Low-Complexity Gaussian Detection for MIMO Systems by Tianbin Wo, Peter Adam Hoeher

“…Using factor graphs as a general framework and applying the Gaussian approximation, three low-complexity iterative detection algorithms are derived, and their performances are compared by means of Monte Carlo simulations. …”
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An adaptive radial object recognition algorithm for lightweight drones in different environments by S. Song, J. Liu, M.P. Shleimovich, R.M. Shakirzyanov, S.V. Novikova

“…The methods are also suitable for unmanned vehicles traveling at high speed, where image processing must be performed in real-time. The proposed algorithms are robust to noise. When combined into a single group, the developed algorithms constitute a customizable set capable of adapting to different imaging conditions and computing power. …”
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Deep Learning Algorithm for Optimized Sensor Data Fusion in Fault Diagnosis and Tolerance by M. Elhoseny, Deepak Dasaratha Rao, Bala Dhandayuthapani Veerasamy, Noha Alduaiji, J. Shreyas, Piyush Kumar Shukla

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Enhancing Performance of Credit Card Model by Utilizing LSTM Networks and XGBoost Algorithms by Kianeh Kandi, Antonio García-Dopico

“…This research paper presents novel approaches for detecting credit card risk through the utilization of Long Short-Term Memory (LSTM) networks and XGBoost algorithms. …”
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Dimensionality cutback and deep learning algorithms efficacy as to the breast cancer diagnostic dataset by Gennady Chuiko, Denys Honcharov

“…Various medical imaging techniques, such as mammography, computed tomography, histopathology, and ultrasound, are contemporary approaches for detecting and classifying breast cancer. Machine learning professionals prefer Deep Learning algorithms when analyzing substantial medical imaging data. …”
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Research on cardiac image segmentation algorithm based on improved level set modeling by Shuaishuai ZHANG, Ruixia LIU, Ke SHAN, Zhenhua GUO

“…In contrast, the proposed approach breaks down a complex problem into several simpler sub-problems that can be solved sequentially to enable faster and more accurate resolution using the ADMM algorithm. …”
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Automatic Generation of Synthesisable Hardware Description Language Code of Multi-Sequence Detector Using Grammatical Evolution by Bilal Majeed, Rajkumar Sarma, Ayman Youssef, Douglas Mota Dias, Conor Ryan

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Algorithm for non-invasive diagnosis of obliterating coronary atherosclerosis based on imaging and laboratory markers by O. M. Drapkina, V. A. Metelskaya, M. V. Dubinskaya, E. B. Yarovaya

“…The sequential passage of algorithm steps by the patient increases the detection rate of coronary atherosclerosis of any degree by 12,2 times, and by 13,8 times in case of severe involvement.Conclusion. …”
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A multimodal approach for ADHD with coexisting ASD detection for children by Jungpil Shin, Sota Konnai, Md. Maniruzzaman, Yoichi Tomioka, Yong Seok Hwang, Akiko Megumi, Akira Yasumura

“…The potentiality of these features was evaluated using Sequential Forward Floating Selection (SFFS)-based algorithm and support vector machine (SVM) was employed to evaluate the performance of ZL and PL tasks. …”
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Optimizing micro cold storage for detecting stale food and fruits by Arun Sreelekha, Amit Wagle Shivali, Nambiar Prahas, Panalkar Pratham, Ekka Prince, Kumar Vaibhav, Dhiman Harsh, Roy Anindita

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Self‐Learning e‐Skin Respirometer for Pulmonary Disease Detection by Anand Babu, Getnet Kassahun, Isabelle Dufour, Dipankar Mandal, Damien Thuau

“…To empower the eSR with early diagnosis functionality, self‐learning capability is further added by integrating the respirometer with the machine learning algorithms. Among various tested algorithms, gradient boosting regression emerges as the most suitable, leveraging sequential model refinement to achieve an accuracy exceeding 95% in detection of chronic obstructive pulmonary diseases (COPD). …”
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TRANSFER LEARNING MODELS COMPARISON FOR DETECTING AND DIAGNOSING SKIN CANCER by Peshraw Ahmed Abdalla, Abdalbasit Mohammed Qadir, Omed Jamal Rashid, Sarkhel H. Taher Karim, Bashdar Abdalrahman Mohammed, Karzan Jaza Ghafoor

“…Therefore, deep neural network techniques are used to create an automated and computerized mechanism for detecting skin illnesses. To identify and diagnose skin illnesses over a range of criteria several neural network algorithms are evaluated and tested in the suggested model to see how well they perform. …”
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Anomaly detection in virtual machine logs against irrelevant attribute interference. by Hao Zhang, Yun Zhou, Huahu Xu, Jiangang Shi, Xinhua Lin, Yiqin Gao

“…The LADSVM approach excels at detecting anomalies in virtual machine logs characterized by strong sequential patterns and noise. …”
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Global Feature Focusing and Information Enhancement Network for Occluded Pedestrian Detection by ZHENG Kaikui, JI Kangyou, LI Jun, LI Qiming

“…ObjectivePedestrian detection is a crucial task in computer vision, especially in applications like autonomous driving, robot navigation, and intelligent surveillance. …”
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