Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML by Ayush Garg (21090944)

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Clinical diagnostic efficacy comparison of the proposed hybrid model and benchmark machine learning models. Metrics are reported as point estimates with 95% CIs. This table offers... by Medhat A. Tawfeek (22522087)

Accumulative reward (s1 = 10, s2 = 10, s3 = 10, t = 10). by Yoshitomi Harada (22311475)

Data Sheet 1_Machine-learning detection of stress severity expressed on a continuous scale using acoustic, verbal, visual, and physiological data: lessons learned.pdf by Marketa Ciharova (8991782)

“…</p>Methods<p>We conducted a preliminary exploration of performance of a machine-learning algorithm trained on multimodal data, namely visual, acoustic, verbal, and physiological features, in its ability to detect stress severity following a partially automated online version of the Trier Social Stress Test. …”

Nonadjacent dependency learning in Swiss toddlers (Bodard et al., 2025) by Julie Bodard (21715023)

“…However, there are few studies with French-speaking children, and none using artificial language learning methodologies.</p><p dir="ltr"><b>Method: </b>We investigated the acquisition of NADs in 18-month-old (<i>n</i> = 30) and 27-month-old (<i>n</i> = 32) monolingual French-learning children in an adaptation of Gómez (2002) artificial grammar learning study to a central fixation eye-tracking paradigm. …”

Architecture of proposed StyleGAN for data augmentation. by Afira Aslam (21433666)

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Architecture of the MobileNet proposed for feature extraction. by Afira Aslam (21433666)

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VGG16 Architecture with detailed list of parameters for automated feature extraction. by Afira Aslam (21433666)

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Grad-CAM visualizations illustrating model interpretability for cotton disease classification on samples from Plant Village dataset [59]. by Afira Aslam (21433666)

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Representative sample images from each category used in the multi-class classification task. by Afira Aslam (21433666)

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Segmentation results obtained from SAM on cotton leaf image. by Afira Aslam (21433666)

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Confusion matrix for the proposed ensemble classifier. by Afira Aslam (21433666)

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Flowchart of the proposed model for automated detection of cotton crop disease. by Afira Aslam (21433666)

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Results of multiple segmentation on single leaf image using SAM. by Afira Aslam (21433666)

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Information of dataset with number of images in each class for training, validation, and testing. by Afira Aslam (21433666)

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MobileNetV2 architecture with detailed list of parameters for automated features extraction. by Afira Aslam (21433666)

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The whole leaf image segmented using SAM. by Afira Aslam (21433666)

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Cotton production in major countries. by Afira Aslam (21433666)

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Segment Anything Model (SAM) framework for segmentation of cotton crop leaves. by Afira Aslam (21433666)

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Table 1_Student wellbeing during COVID-19—Impact of individual characteristics, learning behavior, teaching quality, school system-related aspects and home learning environment.pdf... by Julian Brauchle (20788490)

“…However, the influence of individual or contextual factors on student wellbeing has hardly been investigated to date.</p>Methods<p>In the present study, we used a cross-sectional survey design to examine the impact of individual student characteristics and learning behavior, teaching quality, school system-related aspects and home learning environment on the wellbeing of N = 1,212 secondary school students from Germany and Switzerland (grade level: 5–13; age: 10–20) during the pandemic. …”