ARCHIVES

1. K. Dhara Vath, V. Tejaswi, E. S. P. Kumar, and V. S. Pratham, “Deep Learning based Intelligent Alert System for Visually Impaired People,”
2023 International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2023, pp. 1-6, Doi:
10.1109/ICCCI56745.2023.10128277.
2. Xuhui Hu, Aiguo Song, Zaikai Wei and Hong Zeng, “Stereo Pilot: A Wearable Target Location System for Blind and Visually Impaired
Using Spatial Audio Rendering,” in IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 30, pp. 1621-1630, 2022,
Doi: 10.1109/TNSRE.2022.3182661.
3. Aicha Gourbi, Haythem Ghazouani, and Walid Barhoumi, “Driver Drowsiness Detection Based on Joint Monitoring of Yawning, Blinking
and Nodding,” in 2020 IEEE 16th International Conference on Intelligent Computer Communication and Processing (ICCP), 2020, DOI:
10.1109/ICCP51029.2020.9266160.
4. Jalendra Singh, “Deep Learning Based Driver Drowsiness Detection Model,” in 2020 3rd International Conference on Intelligent Sustainable
Systems (ICISS), India, 2020, DOI: 10.1109/ICISS49785.2020.9316131.
5. Ajzen Joshi, Survi Kyal, Sandipan Banerjee, Taniya Mishra, “In-the-wild Drowsiness Detection from Facial Expressions,” Paper from HSIM
Workshop at IEEE Intelligent Vehicles Symposium 2020 (IV2020), https://doi.org/10.48550/arXiv.2010.11162.
6. P. Murugesapillai, Rd. Manimegalai, “Complex Background and Foreground Extraction in Colour Document Images using Interval Type-2
Fuzzy,” International Journal of Computer Applications Foundation of Computer Science (FCS), NY, USA, Volume 25 – Number 2, 2011,
Doi: 10.5120/3006-4054.
7. Neelam Labhade-Kumar, Mangala S. Biradar, Ashvini Narayan Pawale, “Reinforcement Learning-Based Deep FEFM for Blockchain
Consensus Mechanism Optimization with Non-Linear Analysis,” Journal of Computational Analysis and Applications, vol. 33, no. 05, 2024.
8. Neelam Labhade-Kumar, “Shot Boundary Detection Using Artificial Neural Network,” Advances in Signal and Data Processing, Lecture
Notes in Electrical Engineering, Springer, vol. 703, pp. 44–55, Jan. 2021.
9. Neelam Labhade-Kumar, “Optimizing Cluster Head Selection in Wireless Sensor Networks Using Mathematical Modeling and Statistical
Analysis of the Hybrid Energy-Efficient Distributed (HEED) Algorithm,” Communications on Applied Nonlinear Analysis, ISSN: 1074-
133X, vol. 31, no. 6s, pp. 602–617, Aug. 2024.
10. Neelam Labhade-Kumar, “Experimental Design of Electricity Theft Detection and Alert System Using Arduino Assisted Controller and
Smart Sensors,” 7th International Conference on Inventive Computation Technologies (ICICT), IEEE, 2024, pp. 1961–1968.
11. Neelam Labhade-Kumar, “Novel Management Trends Using IoT in Indian Automotive Spares Manufacturing Industries,” Journal of
Pharmaceutical Negative Results, vol. 13, no. 09, pp. 4887–4899, Nov. 2022.
12. Neelam Labhade-Kumar, “Adaptive Hybrid Bird Swarm Optimization Based Efficient Transmission in WSN,” Journal of Pharmaceutical
Negative Results, vol. 14, no. 02, pp. 480–484, Jan. 2023.
13. Neelam Labhade-Kumar, “Combining Hand-crafted Features and Deep Learning for Automatic Classification of Lung Cancer on CT Scans,”
Journal of Artificial Intelligence and Technology, 2023.
14. Neelam Labhade-Kumar, “Enhancing Crop Yield Prediction in Precision Agriculture through Sustainable Big Data Analytics and Deep
Learning Techniques,” Carpathian Journal of Food Science and Technology, Special Issue, pp. 1–18, 2023.
15. Neelam Labhade-Kumar, “Accident Prevention and Management System in Urban VANET for Improving Slippery Roads Ride After Rain,”
Journal of Environmental Protection and Ecology, ISSN: 1311-5065, vol. 25, no. 2, pp. 586–599, 2024.
16. Neelam Labhade-Kumar, “An Image Processing Method for Kidney Stone Segmentation in CT Scan Images Based on CNN-Regularized
Extreme Learning Machine Approach,” Hybrid and Advanced Technologies, 2023.