This paper proposes an efficient hierarchical solution framework, null-space guidance vector field (NSGVF) with deep reinforcement learning (DRL) based coefficient adjustment, to solve the problem of obstacle avoidanc...
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With the rapid development of the civil aviation industry, the number of civil aviation passengers continues to increase. However, it also brings new challenges to the crowd control capability of airports. Predicting ...
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This study explores the development and assessment of an advanced skin cancer classification system utilizing deep learning techniques for accurate discrimination among diverse skin cancer types. The primary aim is to...
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Acute Lymphoblastic Leukemia (ALL) is a fast progressing cancer that affects white blood cells and requires precise and timely diagnosis for treatment. Current methods of diagnosis are manual and based on histopatholo...
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Distributed Denial Service of Service (DDoS) is very sophisticated attack which brute-force packet jamming to a network to render it useless, if done with large number of nodes. It can be easily countered by a number ...
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Knowledge graphs have emerged as powerful tools for representing and organizing information in a structured and interconnected manner. In this research, we aim to build a knowledge graph and a recommendation system fo...
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In recent years, researchers have proposed a variety of machine learning and deep learning-based techniques to process EEG signals, such as support vector machines, deep learning algorithms, and graph neural networks ...
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Social influence is an individual's ability to change the thoughts or behaviors of others due to factors such as social status, social connections, and social wealth. Studying social influence, especially modeling...
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Significant advancement has been achieved in medical reasoning (Artificial intelligence). However, the interpretability and confidence of many deep learning model discovery ideas face difficulties in fundamental appli...
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With the increasing amount of data,there is an urgent need for efficient sorting algorithms to process large data *** sorting algorithms have attracted much attention because they can take advantage of different hardw...
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With the increasing amount of data,there is an urgent need for efficient sorting algorithms to process large data *** sorting algorithms have attracted much attention because they can take advantage of different hardware's *** the traditional hardware sort accelerators suffer“memory wall”problems since their multiple rounds of data transmission between the memory and the *** this paper,we utilize the in-situ processing ability of the ReRAM crossbar to design a new ReCAM array that can process the matrix-vector multiplication operation and the vector-scalar comparison in the same array *** this designed ReCAM array,we present ReCSA,which is the first dedicated ReCAM-based sort *** hardware designs,we also develop algorithms to maximize memory utilization and minimize memory exchanges to improve sorting *** sorting algorithm in ReCSA can process various data types,such as integer,float,double,and *** also present experiments to evaluate the performance and energy efficiency against the state-of-the-art sort *** experimental results show that ReCSA has 90.92×,46.13×,27.38×,84.57×,and 3.36×speedups against CPU-,GPU-,FPGA-,NDP-,and PIM-based platforms when processing numeric data *** also has 24.82×,32.94×,and 18.22×performance improvement when processing string data sets compared with CPU-,GPU-,and FPGA-based platforms.
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