Search Results - (( using optimization method algorithm ) OR ( features motion learning algorithm ))

Particle swarm optimization with deep learning for human action recognition by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…This decreases the detection efficiency and degrades the target tracking output. Also, the current motion target detection algorithms extract features from the relevant object only if the moving object has complex texture features. …”
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The classification of wink-based eeg signals by means of transfer learning models by Jothi Letchumy, Mahendra Kumar

“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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Sleep arousal events detection using PNN-GBMO classifier based on EEG and ECG signals: A hybrid-learning model by Afsoon Badiei, Saeed Meshgini, Ali Farzamnia

“…A subset of the features is then applied into the probabilistic neural network optimized by Gases Brownian Motion Optimization (GBMO) algorithm. …”
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Machine learning application in predicting anterior cruciate ligament injury among basketball players by Longfei, Guo

“…SHAP analysis identified key feature with the highest predictive value for ACL injury during specific sports motions. …”
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Development of electromyography-controlled 3D printed robot hand and supervised machine learning for signal classification by Abdul Wahit, Mohamad Aizat

“…In conclusion, the electromyography controlled hand robot prototype was successfully developed with improved features, optimal structural durability, higher accurate movement capability, reliable system and lower number of sensor used with higher accuracy of the signal pattern classification.…”
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Fish Motion Trajectories Detection Algorithm Based on Spiking Neural Network (S/O: 12893) by Yusoff, Nooraini, Yusof, Yuhanis, Siraj, Fadzilah, Ahmad, Farzana Kabir

“…The spike encoding was used for feature extraction. The algorithm for this learning model adopted the reward-modulated STDP. …”
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Study of machine learning in computer vision using Raspberry Pi by Chong, Kah Luo

Design and optimization of Levenberg-Marquardt based Neural Network Classifier for EMG signals to identify hand motions by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

“…Between the Levenberg-Marquardt and scaled conjugate gradient learning algorithms, the aforesaid algorithm shows better classification performance. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Hand gesture recognition in ASD related motion using YOLOv8 algorithm / Muhammad Afiq Mohd Ali by Mohd Ali, Muhammad Afiq

“…To enhance recognition accuracy, integration of other motion features that involved body posture and facial expressions should be completed. …”
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Multi-sensor fusion and deep learning framework for automatic human activity detection and health monitoring using motion sensor data / Henry Friday Nweke by Henry Friday , Nweke

“…This is further worsen by the use of single sensors modality and machine learning algorithms. Furthermore, developing robust and efficient methods are required to handle issues such as orientation and position displacement, sensor fusion and feature incompatibility, automatic feature representation, and how to minimize intra-class similarity and inter-class variability. …”
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Design and performance analysis of artificial neural network for hand motion detection from EMG signals by Ibrahimy, Muhammad Ibn, Ahsan, Md. Rezwanul, Khalifa, Othman Omran

“…The conventional and most effective time and timefrequency based features are extracted and normalized. The neural network has been trained with the normalized feature set with supervised learning method. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

“…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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Lightweight spatial attentive network for vehicular visual odometry estimation in urban environments by Gadipudi, N., Elamvazuthi, I., Lu, C.-K., Paramasivam, S., Su, S.

“…On the other hand, learning-based methods automatically learn the features required through motion mapping. …”
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Wearable Sensor Feature Fusion for Human Activity Recognition (HAR) : A Proposed Classification Framework by Norfadzlan, Yusup, Adnan Shahid, Khan, Izzatul Nabila, Sarbini, Nurul Zawiyah, Mohamad

“…Human Activity Recognition (HAR) focuses on detecting people's daily regular activities based on time-series recordings of their actions or motions. Due to the extensive feature engineering and human feature extraction required by traditional machine learning algorithms, they are time consuming to develop. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…The algorithms using convolution features and multi-features fusion algorithms have more advantages in tracking accuracy than the algorithm using a single feature, but the tracking speed will also drop rapidly. …”
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Imitation learning through self-exploration : from body-babbling to visuomotor association / Farhan Dawood by Dawood, Farhan

“…The results show that the imitation learning algorithm is able to incrementally learn and associate the observed motion patterns based on the segmentation of motion primitives.…”
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Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Genetic algorithm method was one of the methods that were widely used in solving optimization problem. …”
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Feature-based stereo vision relative positioning strategy for formation control of unmanned aerial vehicles by Yaghoobi, Yousef, Bahiki, Muhammad Rijaluddin, Syaril Azrad

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A Reinforcement Learning Based Adaptive ROI Generation for Video Object Segmentation by Usmani, U.A., Watada, J., Jaafar, J., Aziz, I.A., Roy, A.

“…The primary focus of the current deep learning-based models is to learn the discriminative representations in the foreground over motion and appearance in small-term temporal segments. …”
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