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Adel Belkhiri and Michel Dagenais
The graphics processing unit (GPU) plays a crucial role in boosting application performance and enhancing computational tasks. Thanks to its parallel architecture and energy efficiency, the GPU has become essential in many computing scenarios. On the oth...
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Xiaoyu Han, Chenyu Li, Zifan Wang and Guohua Liu
Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML). Although search methods based on reinforcement learning and evolutionary ...
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Eun-Seok Lee and Byeong-Seok Shin
The extended reality (XR) environment demands high-performance computing and data processing capabilities, while requiring continuous technological development to enable a real-time integration between the physical and virtual worlds for user interaction...
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Xinjing Zhang and Qixun Zhou
Human pose estimation, as the basis of advanced computer vision, has a wide application perspective. In existing studies, the high-capacity model based on the heatmap method can achieve accurate recognition results, but it encounters many difficulties wh...
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Weison Lin, Yajun Zhu and Tughrul Arslan
Edge AI accelerators are utilized to accelerate the computation in edge AI devices such as image recognition sensors on robotics, door lockers, drones, and remote sensing satellites. Instead of using a general-purpose processor (GPP) or graphic processin...
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Vuka?in Stanojevic, Lev Kazakovtsev, Predrag S. Stanimirovic, Natalya Rezova and Guzel Shkaberina
In this work, we consider the problem of calculating the generalized Moore?Penrose inverse, which is essential in many applications of graph theory. We propose an algorithm for the massively parallel systems based on the recursive algorithm for the gener...
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Rina Komatsu and Tad Gonsalves
In CycleGAN, an image-to-image translation architecture was established without the use of paired datasets by employing both adversarial and cycle consistency loss. The success of CycleGAN was followed by numerous studies that proposed new translation mo...
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Valentin Ogrean and Remus Brad
Since their inception, deep-learning architectures have shown promising results for automatic segmentation. However, despite the technical advances introduced by fully convolutional networks, generative adversarial networks or recurrent neural networks, ...
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Seojin Jang, Wei Liu and Yongbeom Cho
Owing to their high accuracy, deep convolutional neural networks (CNNs) are extensively used. However, they are characterized by high complexity. Real-time performance and acceleration are required in current CNN systems. A graphics processing unit (GPU)...
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Mirco De Marchi, Francesco Lumpp, Enrico Martini, Michele Boldo, Stefano Aldegheri and Nicola Bombieri
Many modern programmable embedded devices contain CPUs and a GPU that share the same system memory on a single die. Such a unified memory architecture (UMA) allows programmers to implement different communication models between CPU and the integrated GPU...
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