Deep learning models have demonstrated their effectiveness in capturing complex relationships between input features and target outputs across many different application domains.These models, however, often come with considerable memory and computational demands, posing challenges for deployment on resource-constrained edge devices.Knowledge distil
Since the traditional base station inspection of telecom operators is enforced manually now,it not only consumes manpower,but also has many problems,such as safety,unverifiable result,and incomplete information weight and so on.The application practice and challenge of artificial intelligence technology in base station routine inspection of operato
The rising industrial demand for technological advancement in improving their working fluids and thermal augmentation has prompted studies on various non-Newtonian fluids and nanofluids.These play momentous role in many engineering devices and electronics development.Therefore, this M Sandals study seeks to examine the thermal performance of ternar
The development of autonomous driving models through reinforcement learning has gained significant traction.However, developing obstacle avoidance systems remains a challenge.Specifically, optimising path completion times while navigating obstacles is an underexplored research area.Amazon Web Services (AWS) DeepRacer emerges as a powerful Mounts in
BackgroundGlaucoma is a leading cause of irreversible blindness globally and for weight decades, Molteno and Ahmed glaucoma implants, operating on different mechanisms, have been used to treat complicated glaucoma with varying success.ObjectiveTo assess the safety and efficacy of the Molteno glaucoma implant (MGI) versus the Ahmed glaucoma valve (A