Artificial Intelligence Accelerators

Mishra, Ashutosh; Yadav, Pamul; Kim, Shiho

doi:10.1007/978-3-031-22170-5_1

Cited by 5 publications

(2 citation statements)

References 52 publications

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“…The Jetson AGX Xavier was selected to be the main target embedded device for our system because it is the first device to feature both tensor cores and two DLA cores, and it is capable of high performance at high power efficiency, relatively affordable, and well-supported by the Jetpack software development kit. A tensor core is a specialized processing unit in an NVIDIA GPU since the Volta architecture, and is designed to accelerate convolutions and matrix operations in deep learning and high-performance computing by using lower-precision formats [39]. The NVIDIA DLA is an open hardware architecture designed for deep learning inference with high power efficiency.…”

Section: ) Optimization On the Jetson Agx Xaviermentioning

confidence: 99%

Optimizing Monocular Driving Assistance for Real-Time Processing on Jetson AGX Xavier

Nguyen,

Nguyen-Ngoc Tran,

Pham

et al. 2024

IEEE Access

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While computer vision and computing technology advances have facilitated advanced driver assistance applications, systems with multi-task design remain highly demanding to operate at high speed on resourceconstrained devices. Our study addresses this challenge by proposing a real-time driver assistance solution specifically developed for a single Jetson AGX Xavier embedded device. It simultaneously performs lane detection, traffic object detection and recognition, and rule-based scene analysis. To achieve high throughput (up to 43 frames per second) without reliance on additional hardware or cloud server, the system exploits Jetson device's specialized AI accelerator and employs various optimization techniques: multithreaded programming, the TensorRT framework, and post-training quantization. The modular design integrates stateof-the-art task-specific methods and ensures adaptation to diverse traffic scenarios across countries as well as future hardware and solutions. Experimental results using a Korean dashcam traffic dataset validated the system's effectiveness and practicality.INDEX TERMS Advanced driver assistance system (ADAS), autonomous driving, edge device, real-time.

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Section: ) Optimization On the Jetson Agx Xaviermentioning

confidence: 99%

Optimizing Monocular Driving Assistance for Real-Time Processing on Jetson AGX Xavier

Nguyen,

Nguyen-Ngoc Tran,

Pham

et al. 2024

IEEE Access

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“…Those algorithms demand an intensive CPU and memory, which prevents standard CPUs from achieving the desired performance levels. 45 As a result, hardware processors, specifically field-programmable gate arrays (FPGAs) platforms, have been used to effectively maximize those models' performance. [46][47][48] FPGA is an integrated circuit customized for a specific application where the configuring process is applied after manufacturing.…”

Section: Artificial Intelligence (Ai) For Healthcarementioning

confidence: 99%

Contemporary Role and Applications of Artificial Intelligence in Dentistry

Bonny,

Al Nassan,

Obaideen

et al. 2023

F1000Res

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Artificial Intelligence (AI) technologies play a significant role and significantly impact various sectors, including healthcare, engineering, sciences, and smart cities. AI has the potential to improve the quality of patient care and treatment outcomes while minimizing the risk of human error. Artificial Intelligence (AI) is transforming the dental industry, just like it is revolutionizing other sectors. It is used in dentistry to diagnose dental diseases and provide treatment recommendations. Dental professionals are increasingly relying on AI technology to assist in diagnosis, clinical decision-making, treatment planning, and prognosis prediction across ten dental specialties. One of the most significant advantages of AI in dentistry is its ability to analyze vast amounts of data quickly and accurately, providing dental professionals with valuable insights to enhance their decision-making processes. The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties; dental public health, endodontics, oral and maxillofacial surgery, oral medicine and pathology, oral & maxillofacial radiology, orthodontics and dentofacial orthopedics, pediatric dentistry, periodontics, prosthodontics, and digital dentistry in general. We will also show the pros and cons of using AI in all dental specialties in different ways. Finally, we will present the limitations of using AI in dentistry, which made it incapable of replacing dental personnel, and dentists, who should consider AI a complimentary benefit and not a threat.

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