With the rapid growth of real-world graphs,the size of which can easily exceed the on-chip(board)storage capacity of an accelerator,processing large-scale graphs on a single Field Programmable Gate Array(FPGA)becomes ...
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With the rapid growth of real-world graphs,the size of which can easily exceed the on-chip(board)storage capacity of an accelerator,processing large-scale graphs on a single Field Programmable Gate Array(FPGA)becomes *** multi-FPGA acceleration is of great necessity and *** cloud providers(e.g.,Amazon,Microsoft,and Baidu)now expose FPGAs to users in their data centers,providing opportunities to accelerate large-scale graph *** this paper,we present a communication library,called FDGLib,which can easily scale out any existing single FPGA-based graph accelerator to a distributed version in a data center,with minimal hardware engineering *** provides six APIs that can be easily used and integrated into any FPGA-based graph accelerator with only a few lines of code *** the torus-based FPGA interconnection in data centers,FDGLib also improves communication efficiency using simple yet effective torus-friendly graph partition and placement *** interface FDGLib into AccuGraph,a state-of-the-art graph *** results on a 32-node Microsoft Catapult-like data center show that the distributed AccuGraph can be 2.32x and 4.77x faster than a state-of-the-art distributed FPGA-based graph accelerator ForeGraph and a distributed CPU-based graph system Gemini,with better scalability.
The extensive spread of DeepFake images on the internet has emerged as a significant challenge, with applications ranging from harmless entertainment to harmful acts like blackmail, misinformation, and spreading false...
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In the robust IoT based system design, it is hard to make decisions incorporate the environmental sound features as well as to incorporate dynamic and noise resilient environments into the system. The development in t...
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Automated lymphocyte segmentation from smear images plays an important role in disease diagnosis and monitoring, aiding in the assessment of immune system function and pathology detection. This study proposes an appro...
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Confusing object detection(COD),such as glass,mirrors,and camouflaged objects,represents a burgeoning visual detection task centered on pinpointing and distinguishing concealed targets within intricate backgrounds,lev...
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Confusing object detection(COD),such as glass,mirrors,and camouflaged objects,represents a burgeoning visual detection task centered on pinpointing and distinguishing concealed targets within intricate backgrounds,leveraging deep learning *** garnering increasing attention in computer vision,the focus of most existing works leans toward formulating task-specific solutions rather than delving into in-depth analyses of methodological *** of now,there is a notable absence of a comprehensive systematic review that focuses on recently proposed deep learning-based models for these specific *** fill this gap,our study presents a pioneering review that covers both themodels and the publicly available benchmark datasets,while also identifying potential directions for future research in this *** current dataset primarily focuses on single confusing object detection at the image level,with some studies extending to video-level *** conduct an in-depth analysis of deep learning architectures,revealing that the current state-of-the-art(SOTA)COD methods demonstrate promising performance in single object *** also compile and provide detailed descriptions ofwidely used datasets relevant to these detection *** endeavor extends to discussing the limitations observed in current methodologies,alongside proposed solutions aimed at enhancing detection ***,we deliberate on relevant applications and outline future research trajectories,aiming to catalyze advancements in the field of glass,mirror,and camouflaged object detection.
The key issue of session-based recommendation (SBR) is how to efficiently predict the next interaction item based on the item sequence of anonymous users. In order to mine the complex multivariate relationship between...
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Good communication is essential in a world where connections are becoming more and more blurred. But traditional communication barriers are magnified for the community of hearing-impaired people, highlighting the need...
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computer vision-based surveillance is very important today's security systems to detect, track and regulate the security much better than standard cameras. However, like any other performance measurement systems t...
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DCD (Developmental Coordination Disorder) has become a global problem, and several studies have shown that early detection and intervention are important for the prevention and treatment of DCD in children. To address...
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COVID-19 (Coronavirus disease of 2019) is caused by SARS-CoV2(Severe Acute Respiratory Syndrome Coronavirus 2) and it was first diagnosedin December 2019 in China. As of 25th Aug 2021, there are 165 million con-firmed...
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COVID-19 (Coronavirus disease of 2019) is caused by SARS-CoV2(Severe Acute Respiratory Syndrome Coronavirus 2) and it was first diagnosedin December 2019 in China. As of 25th Aug 2021, there are 165 million con-firmed COVID-19 positive cases and 4.4 million deaths globally. As of today,though there are approved COVID-19 vaccine candidates only 4 billion doseshave been administered. Until 100% of the population is safe, no one is safe. Eventhough these vaccines can provide protection against getting seriously ill anddying from the disease, it does not provide 100% protection from getting infectedand passing it on to others. The more the virus spreads;it has more opportunity tomutate. So, it is mandatory to follow all precautions like maintaining social distance, wearing mask, washing hands frequently irrespective of whether a person isvaccinated or not. To prevent spread of the virus, contact tracing based on socialdistance also becomes equally important. The work proposes a solution that canhelp with contact tracing/identification, knowing the infected persons recent travelhistory (even within the city) for few days before being assessed positive. Whilethe person would be able to give the known contacts with whom he/she has interacted with, he/she will not be aware of who all were in proximity if he/she hadbeen in public places. The proposed solution is to get the CCTV (Closed-CircuitTelevision) video clips from those public places for the specific date and time andidentify the people who were in proximity—i.e., not followed the safe distance tothe infected person. The approach uses YOLO V3 (You Only Look Once) whichuses darknet framework for people detection. Once the infected person is locatedfrom the video frames, the distance from that person to the other people in theframe is found, to check if there is a violation of social distance guideline. If thereis, then the people violating the distance are extracted and identified using Facialdetection and recognitio
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