Comparative classification performance using VGG, ResNet, and ViT models, with each model applied in two different training approaches on segmented cells: trained from scratch and... by Oriana Presacan (22232246)

Supplementary file 1_Towards standardizing mitral transcatheter edge-to-edge repair with deep-learning algorithm: a comprehensive multi-model strategy.docx by Silvia Corona (22678994)

“…</p>Results<p>Preliminary results on test sets showed 95.7% accuracy in TTE view classification and 91% accuracy for TEE view classification. …”

Visualization of comparative experiment results. The content within the red line box demonstrates the various performances of semantic segmentation. by Bo Liu (127343)

Subjects:

Average CA for HT, FWHT, BP, and SF-based features extracted from 2.4-second time segments using the k-NN classifier. by Ebru Ergün (21395498)

Confusion matrix for multiclass classification. by Ebru Ergün (21395498)

“…To optimize system accuracy and speed, EEG and NIRS data were segmented into discrete temporal windows. Features were extracted using the Hilbert Transform, while classification was performed via the k-nearest neighbor algorithm. …”

LENA ASP validation for adult and child segments (Meera et al., 2025) by Shoba S. Meera (20329597)

“…Thus, the current study aims to validate the classification accuracy of the LENA algorithm specifically focusing on speaker recognition of adult segments (AdS) and child segments (ChS) in a sample of bi/multilingual families from India.…”

Illustration of the unrestricted model and its training algorithm. by Yuru Song (21300760)

Average CA Results for 24-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Average CA Results for 12-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Average CA Results for 4.8-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Average CA Results for 2.4-Second Time Segments: a) Training Set and b) Test Set, representing both single and hybrid modalities in terms of percentage. by Ebru Ergün (21395498)

Video 1_Real-time segmentation and phenotypic analysis of rice seeds using YOLOv11-LA and RiceLCNN.mp4 by Dejia Zhang (18526510)

“…Although significant progress has been made using deep learning, particularly convolutional neural networks (CNNs) and attention-based models, earlier methods such as threshold segmentation and single-grain classification faced challenges related to computational efficiency and latency, especially in high-density seed agglutination scenarios. …”

Video 2_Real-time segmentation and phenotypic analysis of rice seeds using YOLOv11-LA and RiceLCNN.mp4 by Dejia Zhang (18526510)

“…Although significant progress has been made using deep learning, particularly convolutional neural networks (CNNs) and attention-based models, earlier methods such as threshold segmentation and single-grain classification faced challenges related to computational efficiency and latency, especially in high-density seed agglutination scenarios. …”

DAC module. by He Meng (33363)

“…For addressing these challenges, we propose a novel deep learning algorithm featuring Dense Atrous Convolution (DAC) and attention mechanism to realize high-precision segmentation and classification of Coronary artery plaques. …”

Ablation experiments. by He Meng (33363)

“…For addressing these challenges, we propose a novel deep learning algorithm featuring Dense Atrous Convolution (DAC) and attention mechanism to realize high-precision segmentation and classification of Coronary artery plaques. …”

Workflow of this paper. by He Meng (33363)

“…For addressing these challenges, we propose a novel deep learning algorithm featuring Dense Atrous Convolution (DAC) and attention mechanism to realize high-precision segmentation and classification of Coronary artery plaques. …”

Improved network used in this paper. by He Meng (33363)

“…For addressing these challenges, we propose a novel deep learning algorithm featuring Dense Atrous Convolution (DAC) and attention mechanism to realize high-precision segmentation and classification of Coronary artery plaques. …”

CBAM attention mechanism. by He Meng (33363)

“…For addressing these challenges, we propose a novel deep learning algorithm featuring Dense Atrous Convolution (DAC) and attention mechanism to realize high-precision segmentation and classification of Coronary artery plaques. …”

State-of-the-Art Skin Disease Classification Using Ensemble Learning and Advanced Image Processing by Nirupama (22148684)

“…The Crayfish Optimization Algorithm with a Reverse Wheel Strategy is applied for an effective feature segmentation, where the most relevant features are segmented. …”

Enhancements to SarcGraph’s z-disc segmentation pipeline. by Saeed Mohammadzadeh (13492285)