Comparative analysis of DDcGAN-GSOM’s Accuracy, Precision, and F1-score. by Nanavath Kiran Singh Nayak (22184565)

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False alarm rate analysis of DDcGAN-GSOM with existing approaches. by Nanavath Kiran Singh Nayak (22184565)

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True positive rate (TPR) analysis of DDcGAN-GSOM with existing techniques. by Nanavath Kiran Singh Nayak (22184565)

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Flow diagram for the proposed methodology. by Nanavath Kiran Singh Nayak (22184565)

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Specificity comparison of DDcGAN-GSOM with prevailing methods. by Nanavath Kiran Singh Nayak (22184565)

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Discriminator loss of suggested technique. by Nanavath Kiran Singh Nayak (22184565)

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Comprehensive comparison of state-of-the-art approaches. by Nanavath Kiran Singh Nayak (22184565)

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Energy consumption analysis of DDcGAN-GSOM with existing methods. by Nanavath Kiran Singh Nayak (22184565)

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Analysis of DDcGAN-GSOM delay with existing techniques. by Nanavath Kiran Singh Nayak (22184565)

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Comparative analysis of DDcGAN-GSOM’s Energy Consumption, Throughput, and Dealy. by Nanavath Kiran Singh Nayak (22184565)

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System model of the proposed method. by Nanavath Kiran Singh Nayak (22184565)

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Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

Dendrogram of the stock prices. by Muhammad Hilal Alkhudaydi (21560690)

“…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”

Descriptive statistics on stock prices. by Muhammad Hilal Alkhudaydi (21560690)

“…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”

Correlation heatmap of the principal components. by Muhammad Hilal Alkhudaydi (21560690)

“…This article uses feature-based models to investigate the primary elements that contribute to the optimal composition of a specific portfolio. …”

tUbenet Foundation Model Weights by Natalie Holroyd (7099391)

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”

Trace, Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry: A Case Study from Single-Cell Metabolomics by Zhichao Liu (191718)

“…However, extraction of trace-abundance signals from complex data sets (<i>m</i>/<i>z</i> value, separation time, signal abundance) that result from ultrasensitive studies requires improved data processing algorithms. …”

Proposed reinforcement learning architecture. by Enoch Solomon (21416703)

“…<div><p>In the realm of game playing, deep reinforcement learning predominantly relies on visual input to map states to actions. The visual data extracted from the game environment serves as the primary foundation for state representation in reinforcement learning agents. …”

Schematic representation of semi-automated algorithm for organoids analyzing. by Anna Demchenko (18449439)