Search Results - adaptive k different ((optimisation algorithm) OR (detection algorithm))

Optimisation and performance evaluation of response surface methodology (RSM), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) in the prediction o... by Chong, D.J.S., Chan, Y.J., Arumugasamy, S.K., Yazdi, S.K., Lim, J.W.

Get full text
Get full text

EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

“…Throughout this research study, models like Support Vector Machine (SVM), K-Nearest Neighbours (KNN) and Adaptive Boosting (AdaBoost) will be explored. …”
Get full text
Get full text

A Hybrid Artificial Intelligence Model for Detecting Keratoconus by Alyasseri Z.A.A., Al-Timemy A.H., Abasi A.K., Lavric A., Mohammed H.J., Takahashi H., Milhomens Filho J.A., Campos M., Hazarbassanov R.M., Yousefi S.

“…This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. …”

A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
Get full text
Get full text

Face recognition for varying illumination and different optical zoom using a combination of binary and geometric features by Khalid, Fatimah, Amjeed, Noor, O.K. Wirza, Rahmita Wirza, Madzin, Hizmawati, Azizan, Illiana

Get full text
Get full text
Get full text

COMPUTER AIDED SYSTEM FOR BREAST CANCER DIAGNOSIS USING CURVELET TRANSFORM by MOHAMED ELTOUKHY, MOHAMED MESELHY

“…The thesis then provides an automatic system for breast cancer detection. An automatic thresholding algorithm was used to separate the area composed of the breast and the pectoral muscle from the background of the image. …”
Get full text
Get full text

Survey on Clustered Routing Protocols Adaptivity for Fire Incidents: Architecture Challenges, Data Losing, and Recommended Solutions by Abbas O.K., Abdullah F., Radzi N.A.M., Salman A.D., Abdulkadir S.J.

A Comprehensive Analysis of Supervised Learning Techniques for Electricity Theft Detection by Bohani F.A., Suliman A., Saripuddin M., Sameon S.S., Md Salleh N.S., Nazeri S.

Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…Firstly, data augmentation is employed in the preprocessing stage to increase the diversity of training samples, thereby improving the model’s robustness and generalization capability. The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
Get full text
Get full text

Techno-economic impact analysis for renewable energy-based hydrogen storage integrated grid electric vehicle charging stations in different potential locations of Malaysia by Roslan M.F., Ramachandaramurthy V.K., Mansor M., Mokhzani A.S., Jern K.P., Begum R.A., Hannan M.A.

“…The results demonstrated favourable outcomes, with the total Net Present Cost (NPC) ranging from $1.4 million to $3.4 million across all locations, and the Cost of Energy (COE) ranging from $0.03/kWh to $0.16/kWh. These findings suggest that the optimization methodology is adaptable for implementation in diverse locations with different meteorological conditions. …”

Development of a phantom and metal artifact correction (MAC) algorithm for post-operative spine computed tomography (CT) imaging / Noor Diyana Osman by Osman, Noor Diyana

“…The missing projection data due to metal region is detected and extracted using an improved technique of dual-step adaptive thresholding. …”
Get full text
Get full text

Simultaneous measurement of multiple soil properties through proximal sensor data fusion: a case study by Wenjun, Ji, Adamchuk, Viacheslav I., Song, Chao Chen, Mat Su, Ahmad S., Ismail, Ashraf, Qianjun, Gan, Zhou, Shi, Biswas, Asim

“…In this field, it was not possible to predict extractable P and K using all tested sensor combinations or algorithms. …”
Get full text
Get full text

Effect of particle size on second law of thermodynamics analysis of Al2O3 nanofluid: Application of XGBoost and gradient boosting regression for prognostic analysis by Kumar K P., Alruqi M., Hanafi H.A., Sharma P., Wanatasanappan V.V.