The first two components extracted from the feature extraction algorithm. by Choon-Hian Goh (14185601)

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Algorithm performance comparison of single sequence features and multiple input sequence features. by Dong Yi (511609)

The extraction results of BRISK and FAST algorithm. by Dongchen Dai (13822355)

The extraction results of ORB and SURF algorithm. by Dongchen Dai (13822355)

Algorithm detection performance. by Kangning Li (6069629)

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Clustering result generated by k-means clustering algorithm using features extracted from t-SNE. by Choon-Hian Goh (14185601)

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Model structure of the Small_obj algorithm. by Kangning Li (6069629)

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Time-frequency feature extraction flowchart. by Minan Tang (20389941)

“…Then, the CPO-CNN classification model is used for feature extraction and feature selection of the time-frequency diagrams and classification of multiple power quality disturbances. …”

Different algorithms for bearing defect detection performance. by Kangning Li (6069629)

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Ablation study on the improved YOLOv5 algorithm. by Kangning Li (6069629)

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Model structural of the improved YOLOv5 algorithm. by Kangning Li (6069629)

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Structure of GRU-CNN feature extraction network. by Qingling Zhang (758713)

Proposed feature extraction technique. by Satria Mandala (8843060)

“…Proposed method, based on a boosting algorithm, namely Fine Tuned Boosting (FTBO) model detects multiple arrhythmia classes. …”

Comparison of average recognition accuracy of different SEI algorithms under different input features. by Dong Yi (511609)

MobileNetV3 feature extraction network structure. by Jianfang Cao (1881379)

Algorithm flow. by Bowen Chen (4631551)

“…Based on the imaging characteristics of LALDA, a multi-channel segmentation (MCS) algorithm is designed. The HSV color space has been transformed, and the image is automatically segmented into multiple sub-regions by mutual calculation of different channels. …”

Average accuracy by feature extraction layer. by Şafak Kılıç (22227019)

“…</p><p>Materials and methods:</p><p>We propose a hybrid architecture integrating ResNet50 backbone with CBAM attention mechanisms, enhanced by a comprehensive deep feature engineering pipeline. The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”

Performance analysis by feature extraction layer. by Şafak Kılıç (22227019)

“…</p><p>Materials and methods:</p><p>We propose a hybrid architecture integrating ResNet50 backbone with CBAM attention mechanisms, enhanced by a comprehensive deep feature engineering pipeline. The framework incorporates multiple feature extraction layers (CBAM, GAP, GMP, pre-final) combined with 10 distinct feature selection methods including Principal Component Analysis (PCA), Chi-square test, Random Forest importance, variance thresholding, and their intersections. …”

Extraction of mesh structure based on smoothing by the opening operation. by Yoshitaka Kimori (7455122)

Algorithm performance in different operational phases. by Dongqing Zhang (423941)