Optimizing performance of feedforward and convolutional neural networks through dynamic activation functions von Rane, Chinmay, Tyagi, Kanishka, Kline, Adrienne, Chugh, Tushar, Manry, Michael

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A novel attention fusion network-based framework to ensemble the predictions of CNNs for lymph node metastasis detection von Rane, Chinmay, Mehrotra, Raj, Bhattacharyya, Shubham, Sharma, Mukta, Bhattacharya, Mahua

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Effect of impeller design and power consumption on crystal size distribution von Rane, Chinmay V., Ekambara, Kalekudithi, Joshi, Jyeshtharaj B., Ramkrishna, Doraiswami

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CFD simulation of stirred tanks: Comparison of turbulence models. Part I: Radial flow impellers von Joshi, Jyeshtharaj B., Nere, Nandkishor K., Rane, Chinmay V., Murthy, B. N., Mathpati, Channamallikarjun S., Patwardhan, Ashwin W., Ranade, Vivek V.

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Synthetic image augmentation with generative adversarial network for enhanced performance in protein classification von Verma, Rohit, Mehrotra, Raj, Rane, Chinmay, Tiwari, Ritu, Agariya, Arun Kumar

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CFD simulation of stirred tanks: Comparison of turbulence models (Part II: Axial flow impellers, multiple impellers and multiphase dispersions) von Joshi, Jyeshtharaj B., Nere, Nandkishor K., Rane, Chinmay V., Murthy, B. N., Mathpati, Channamallikarjun S., Patwardhan, Ashwin W., Ranade, Vivek V.

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CFD simulation and comparison of industrial crystallizers von Rane, Chinmay V., Ganguli, Arijit A., Kalekudithi, Ekambara, Patil, Raosaheb N., Joshi, Jyeshtharaj B., Ramkrishna, Doraiswami

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Multistage Newton’s Approach for Training Radial Basis Function Neural Networks von Tyagi, Kanishka, Rane, Chinmay, Irie, Bito, Manry, Michael

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Synthetic image augmentation with generative adversarial network for enhanced performance in protein classifi cation von Rohit Verma, Raj Mehrotra, Chinmay Rane, Ritu Tiwari, Arun Kumar Agariya

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Automated Sizing and Training of Efficient Deep Autoencoders using Second Order Algorithms von Tyagi, Kanishka, Rane, Chinmay, Manry, Michael

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Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions von Rane, Chinmay, Tyagi, Kanishka, Manry, Michael

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Optimal Input Gain: All You Need to Supercharge a Feed-Forward Neural Network von Rane, Chinmay, Tyagi, Kanishka, Malalur, Sanjeev, Shinge, Yash, Manry, Michael

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Making Sigmoid-MSE Great Again: Output Reset Challenges Softmax Cross-Entropy in Neural Network Classification von Tyagi, Kanishka, Rane, Chinmay, Vaidya, Ketaki, Challgundla, Jeshwanth, Auddy, Soumitro Swapan, Manry, Michael

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Optimizing Performance of Feedforward and Convolutional Neural Networks through Dynamic Activation Functions von Rane, Chinmay, Tyagi, Kanishka, Manry, Michael

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Automated Sizing and Training of Efficient Deep Autoencoders using Second Order Algorithms von Tyagi, Kanishka, Rane, Chinmay, Manry, Michael

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Optimal Input Gain: All You Need to Supercharge a Feed-Forward Neural Network von Rane, Chinmay, Tyagi, Kanishka, Malalur, Sanjeev, Shinge, Yash, Manry, Michael

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Making Sigmoid-MSE Great Again: Output Reset Challenges Softmax Cross-Entropy in Neural Network Classification von Tyagi, Kanishka, Rane, Chinmay, Vaidya, Ketaki, Challgundla, Jeshwanth, Soumitro Swapan Auddy, Manry, Michael

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Financial Portfolio Management and Optimization to Maximize Returns Using a Combination of HRP and Sentiment Analysis von Rane, Chinmay, Pai, Siddhesh, Dani, Mithil, Dhage, Sudhir

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Financial Fraud Detection in Healthcare Using Machine Learning and Deep Learning Techniques von Mehbodniya, Abolfazl, Alam, Izhar, Pande, Sagar, Neware, Rahul, Rane, Kantilal Pitambar, Shabaz, Mohammad, Madhavan, Mangena Venu

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Smartphone-Based mHealth and Internet of Things for Diabetes Control and Self-Management von Mehbodniya, Abolfazl, Suresh Kumar, A., Rane, Kantilal Pitambar, Bhatia, Komal Kumar, Singh, Bhupesh Kumar

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