Gravitating Nano-sensory Drift Towards Deep Learning Analysis, Modelling and Research

The proposed book is centrally focused on Human computer Interaction and how the sensors within the small and wide groups of Nano-robots employ deep learning for applications in industrial applications. It covers a wide array of topics that are useful for the researchers and students to gain knowledge about AI and sensors in nanobots. Furthermore, we will explore deep learning approaches to enhance the accuracy of AI systems applied in medical robotics in surgical techniques. Secondly, we plan to explore bio-nano-robotics, which is a field in nano-robotics, that deals automatic intelligence handling, self-assembly and replication, information processing and programmability .

1. Sensor Driven Data on Medical Images

2. Machine Learning / Deep Learning Approaches Healthcare Environment

3. IoMT using Sensors by Learning Algorithm

4. Big Data advancements in Nano environments

5. Deep learnt Predictive architecture upon Nano-sensors

6. Data Organization for dull web in Nano-particles

7. Next Gen Technology Towards Nanoids

8. Analysis of Sensor node in e-healthcare

9. Nano-robotic predictive architectures upon Nano-sensors

10. Hybrid Environment towards Healthcare

11. ML/DL hardness Problems for sensor nodes.

And many more related topics to Nano technology, DL/ML for IoMT