Real-Time Incompressible Fluid Simulation on the GPU by Xiao Nie, Leiting Chen, Tao Xiang

“…The performance results illustrate that our approach can efficiently simulate realistic incompressible fluid in real time and results in a speed-up factor of up to 23 on a high-end NVIDIA GPU in comparison to single-threaded CPU-based implementation.…”
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CUDT: A CUDA Based Decision Tree Algorithm by Win-Tsung Lo, Yue-Shan Chang, Ruey-Kai Sheu, Chun-Chieh Chiu, Shyan-Ming Yuan

“…In order to improve data processing latency in huge data mining, in this paper, we design and implement a new parallelized decision tree algorithm on a CUDA (compute unified device architecture), which is a GPGPU solution provided by NVIDIA. In the proposed system, CPU is responsible for flow control while the GPU is responsible for computation. …”
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Automatic brake Driver Assistance System based on deep learning and fuzzy logic. by A R García-Escalante, R Q Fuentes-Aguilar, A Palma-Zubia, E Morales-Vargas

“…The implementation uses an NVIDIA Jetson TX2 and a ZED stereo camera for traffic light detection, which, in addition to the depth map provided by the camera and a fuzzy inference system, make the decision to perform automatic braking based on the distance and current state of the traffic light. …”
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Efficient Parallel Implementation of Active Appearance Model Fitting Algorithm on GPU by Jinwei Wang, Xirong Ma, Yuanping Zhu, Jizhou Sun

“…We implement our algorithm using the compute unified device architecture (CUDA) on the Nvidia’s GTX 650 GPU, which has the latest Kepler architecture. …”
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Advanced sensors network in a centralized IoT system using low-cost microcontrollers and automatic configuration by Andrei-Mihai VĂDAN, Liviu-Cristian MICLEA

“…Folosește hardware popular, precum Raspberry Pi, Raspberry Pi Pico, Espressif, Banana Pi, Nvidia Jetson, iar comunicarea între microcontrolere se face într-o rețea Ethernet, cu dispozitive conectate prin cablu sau wirelles. …”
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Deep Learning Techniques in DICOM Files Classification: A Systematic Review by Mabirizi, Vicent, Kawuma, Simon, Natumanya, Deborah, Wasswa, William

“…Frameworks such as MONAI, NVIDIA Clare, SimpleITK, and OpenCV facilitate direct DICOM processing but face limitations, including overfitting, challenges with data heterogeneity, and inefficiencies in handling large datasets. …”
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High-Performance 3D Compressive Sensing MRI Reconstruction Using Many-Core Architectures by Daehyun Kim, Joshua Trzasko, Mikhail Smelyanskiy, Clifton Haider, Pradeep Dubey, Armando Manduca

“…We demonstrate that a CUDA-based code running on an NVIDIA Tesla C2050 GPU can reconstruct a 256 × 160 × 80 volume from an 8-channel acquisition in 19 seconds, which is in itself a significant improvement over the state of the art. …”
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OBTPN: A Vision-Based Network for UAV Geo-Localization in Multi-Altitude Environments by Nanxing Chen, Jiqi Fan, Jiayu Yuan, Enhui Zheng

“…OBTPN was successfully deployed on an NVIDIA Jetson TX2 onboard computer. This paper also proposes a high-altitude complex environment dataset, Crossview9, which addresses a research gap in the field of high-altitude visual navigation. …”
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GPU-Accelerated Parallel FDTD on Distributed Heterogeneous Platform by Ronglin Jiang, Shugang Jiang, Yu Zhang, Ying Xu, Lei Xu, Dandan Zhang

“…In our experiments, 64 NVIDIA TESLA K20m GPUs and 64 INTEL XEON E5-2670 CPUs are used to carry out the pure CPU, pure GPU, and CPU + GPU tests. …”
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The Construction of a Stream Service Application with DeepStream and Simple Realtime Server Using Containerization for Edge Computing by Wen-Chung Shih, Zheng-Yao Wang, Endah Kristiani, Yi-Jun Hsieh, Yuan-Hsin Sung, Chia-Hsin Li, Chao-Tung Yang

“…This paper addresses the increasing demand for efficient and scalable streaming service applications within the context of edge computing, utilizing NVIDIA Jetson Xavier NX hardware and Docker. The study evaluates the performance of DeepStream and Simple Realtime Server, demonstrating that containerized applications can achieve performance levels comparable to traditional physical machines. …”
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ALBERTA: ALgorithm-Based Error Resilience in Transformer Architectures by Haoxuan Liu, Vasu Singh, Michal Filipiuk, Siva Kumar Sastry Hari

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Localization of mobile robot in prior 3D LiDAR maps using stereo image sequence by I.V. Belkin, A.A. Abramenko, V.D. Bezuglyi, D.A. Yudin

“…The method’s performance is demonstrated on different hardware platforms, including energy-efficient Nvidia Jetson Xavier AGX. With parallel code implementation, we achieve an input stereo image processing speed of 14 frames per second on Xavier AGX.…”
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Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation by Quentin Malé, Corentin J. Lapeyre, Nicolas Noiray

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Space mission as a service (SMaaS): General-purpose computing on space by Leonardo Camargo-Forero, Julián G. Rodríguez-Ferreira, Carlos J. Barrios-Hernández

“…Such strategies will include evaluating standard operating systems and embedded companion computers, such as the NVIDIA® Jetson Series, under space conditions, common AI frameworks, High-Performance Embedded Computing, and cloud computing as an integrator between space computing devices and earth ground stations. …”
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A Novel Technique for Handwritten Signature Recognition by Leila Boucerredj, Karima Kechroud, Bouaziz Noureddine, Abderrahmane Khechekhouche

“…Experiments, conducted on a personal computer equipped with an NVIDIA Quadro M1200 GPU, an Intel i7 processor, and 32 GB of RAM, demonstrated the model’s exceptional performance, achieving validation accuracies of 99.60% on the MCYT-75 dataset and 99.80% on the GPDS-300 dataset. …”
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Comparative analysis of neural network models performance on low-power devices for a real-time object detection task by A. Zagitov, E. Chebotareva, A. Toschev, E. Magid

“…The results of experiments provide insights into trade-offs between accuracy, speed, and computational efficiency of MobileNetV2 SSD, CenterNet MobileNetV2 FPN, EfficientDet, YoloV5, YoloV7, YoloV7 Tiny and YoloV8 neural network models on Raspberry Pi 4B, Raspberry Pi 3B and NVIDIA Jetson Nano with TensorFlow Lite. We fine-tuned the models on our custom dataset prior to benchmarking and used post-training quantization (PTQ) and quantization-aware training (QAT) to optimize the models’ size and speed. …”
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PRISM-Med: Parameter-Efficient Robust Interdomain Specialty Model for Medical Language Tasks by Jieui Kang, Hyungon Ryu, Jaehyeong Sim

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Improving Performance of Real-Time Object Detection in Edge Device Through Concurrent Multi-Frame Processing by Seunghwan Kim, Changjong Kim, Sunggon Kim

“…We implement our scheme in YOLO (You Only Look Once), one of the most popular real-time object detection algorithms, on a state-of-the-art, resource-constrained IoT edge device, Nvidia Jetson Orin Nano, using real-world video and image datasets, including MS-COCO, ImageNet, PascalVOC, DOTA, animal videos, and car-traffic videos. …”
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Automated Measurement of Air Bubbles Dispersion in Ice Cream Using Machine Learning Methods by Igor A. Korolev

“…The models were trained using the NVIDIA GTX video accelerator. The review showed that the dispersion of ice cream air phase depends on its composition and the freezing parameters whereas bubble formation is usually described in line with the existing foaming theories. …”
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Development of a handheld GPU-assisted DSC-TransNet model for the real-time classification of plant leaf disease using deep learning approach by Midhun P. Mathew, Sudheep Elayidom, V. P. Jagathy Raj, K. M. Abubeker

“…The developed DSC-TransNet model is deployed in NVIDIA Jetson Nano single board computer. This research contributes to advancing the field of automated plant disease classification, addressing critical challenges in modern agriculture and promoting more efficient and sustainable farming practices.…”
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