The issue of food security continues to be a prominent global concern, affecting a significant
number of individuals who experience the adverse effects of hunger and malnutrition. The …

As the thematic literature of machine learning suggests, reinforcement learning falls
between the two methods of observational learning and non-observational learning. In this …

Video surveillance systems are integral to bolstering safety and security across multiple
settings. With the advent of deep learning (DL), a specialization within machine learning …

Path planning for mobile robots in complex circumstances is still a challenging issue. This
work introduces an improved deep reinforcement learning strategy for robot navigation that …

In this paper, we propose a hybrid centralized training and decentralized execution neural
network architecture with deep reinforcement learning (DRL) to complete the multi-agent …

Efficient navigation is crucial for intelligent mobile robots in complex environments. This
paper introduces an innovative approach that seamlessly integrates advanced machine …

Object recognition algorithms need to be very accurate and efficient in order for autonomous
navigation systems to see and securely interact with their surroundings. Although …

Towards sustainable agriculture: Harnessing AI for global food security Page 1 Towards
sustainable agriculture: Harnessing AI for global food security Dhananjay K. Pandeya,⁎, Richa …

The primary problem at hand revolves around the domain of autonomous robot navigation. It
is framed within the specific scenario of a robot, the SCITOS G5 navigating along the four …

Earthquakes, among the most devastating natural disasters, often leave a trail of destruction,
causing both loss of life and extensive property damage. In response to this ongoing …