Gemini: A Family of Highly Capable Multimodal Models G Team arXiv preprint arXiv:2312.11805, 2023 | 3417 | 2023 |
State-based dynamic graph with breadth first progression for autonomous robots T Chugh, K Tyagi, P Srinivasan, J Challagundla 2024 IEEE 14th Annual Computing and Communication Workshop and Conference …, 2024 | 4 | 2024 |
Multiple gain adaptations for improved neural networks training J Challagundla, K Tyagi, T Chugh, M Manry 2024 IEEE 14th Annual Computing and Communication Workshop and Conference …, 2024 | 3 | 2024 |
Adaptive multiple optimal learning factors for neural network training J Challagundla The University of Texas at Arlington, 2015 | 2 | 2015 |
Improving Small Object Detection with Area-Scaled and Dynamic Focal Loss S Raina, J Challagundla, S Acharya, M Singh 2025 IEEE 15th Annual Computing and Communication Workshop and Conference …, 2025 | | 2025 |
Trajectory Prediction in Autonomous Driving: A Comprehensive Review of Deep Learning Models and Future Direction S Raina, J Challagundla, M Singh 2025 IEEE 15th Annual Computing and Communication Workshop and Conference …, 2025 | | 2025 |
Making Sigmoid-MSE Great Again: Output Reset Challenges Softmax Cross-Entropy in Neural Network Classification K Tyagi, C Rane, K Vaidya, J Challgundla, SS Auddy, M Manry arXiv preprint arXiv:2411.11213, 2024 | | 2024 |