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AA-ResNet: Energy Efficient All-Analog ResNet Accelerator
2020 IEEE 63rd International Midwest Symposium on Circuits and Systems (MWSCAS), 2020High energy efficiency is a major concern for emerging machine learning accelerators designed for IoT edge computing. Recent studies propose in-memory and mixed-signal approaches to minimize energy overhead resulting from frequent memory accesses and extensive digital computation.
Jongyup Lim +10 more
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Proceedings of the 33rd annual ACM SIGUCCS conference on User services, 2005
Wayne State University (WSU) has implemented network registration and management tools. These tools have matured and become very useful to reduce support costs and maintain continuity of network services for our residential network (ResNet) customers.
Stephen Wassef +2 more
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Wayne State University (WSU) has implemented network registration and management tools. These tools have matured and become very useful to reduce support costs and maintain continuity of network services for our residential network (ResNet) customers.
Stephen Wassef +2 more
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Proceedings of the 26th ACM international conference on Multimedia, 2018
With the ever-increasing urbanization process, the traffic jam has become a common problem in the metropolises around the world, making the traffic speed prediction a crucial and fundamental task. This task is difficult due to the dynamic and intrinsic complexity of the traffic environment in urban cities, yet the emergence of crowd map query data ...
Binbing Liao +9 more
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With the ever-increasing urbanization process, the traffic jam has become a common problem in the metropolises around the world, making the traffic speed prediction a crucial and fundamental task. This task is difficult due to the dynamic and intrinsic complexity of the traffic environment in urban cities, yet the emergence of crowd map query data ...
Binbing Liao +9 more
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Adversarial Perturbation with ResNet
Proceedings of the 2020 on Great Lakes Symposium on VLSI, 2020Most of security issues in deep learning are based on human-imperceptible adversarial perturbation, which can fool image recognition models of deep learning and bring a serious security threats to many practical applications. However, how to construct a universal adversarial perturbation for images is still an open question.
Heng Liu +4 more
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Proceedings of the 2018 International Conference on Algorithms, Computing and Artificial Intelligence, 2018
The model Wide & Deep is widely applied for CTR prediction in recommender systems, which unites linear model for memorization and deep neural network for generalization. However, the essence of Wide & Deep still lies in feature engineering, especially in the processing of categorical features, which usually requires manually crafted feature engineering
Xuxu Gao, Hongxia Bie
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The model Wide & Deep is widely applied for CTR prediction in recommender systems, which unites linear model for memorization and deep neural network for generalization. However, the essence of Wide & Deep still lies in feature engineering, especially in the processing of categorical features, which usually requires manually crafted feature engineering
Xuxu Gao, Hongxia Bie
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Deep Embedded Clustering with ResNets
2021 14th International Conference on Human System Interaction (HSI), 2021Clustering is an AI technique that has been successfully applied to the abundance of unlabelled real-world data for revealing hidden patterns and knowledge extraction. Deep Embedded Clustering (DEC) is a deep Autoencoder (AE) based model that learns feature representations and cluster assignments simultaneously.
Chathurika Wickramasinghe +2 more
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MST-ResNet: A Multiscale Spatial Temporal ResNet for Steering Prediction
2019 2nd China Symposium on Cognitive Computing and Hybrid Intelligence (CCHI), 2019Over the years, autonomous driving has attracted more and more interest from academia and industry. The field involves a lot of technologies, including SLAM, object detection and end to end driving decision. In this paper, our goal is to make driving decisions based on visual models, which is a hot topic both in computer vision and autonomous driving ...
Long Wen +4 more
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G-ResNet: Improved ResNet for Brain Tumor Classification
2019The brain tumors, are the most common and aggressive disease, leading to a short life expectancy and much pain. Timely and accurate diagnosis is the key factor in improving the survival rate of patients. The main method of identifying brain tumors is to analyze MR image that provides detailed information about brain structure and anomaly detection in ...
Dunsheng Liu, Yuanning Liu, Liyan Dong
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CO-ResNet: Optimized ResNet model for COVID-19 diagnosis from X-ray images
International Journal of Hybrid Intelligent Systems, 2021This paper focuses on the application of deep learning (DL) based model in the analysis of novel coronavirus disease (COVID-19) from X-ray images. The novelty of this work is in the development of a new DL algorithm termed as optimized residual network (CO-ResNet) for COVID-19.
Bharati, Subrato +3 more
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Outsourcing the student resNet
Proceedings of the 32nd annual ACM SIGUCCS conference on User services, 2004This paper describes the problems Ithaca College faced in continuing to provide service and support for the student residential network (ResNet). It also details the rationale and decision making process to outsource ResNet and outlines the timeline of events needed to make the change by the beginning of the Fall 2004 semester.
Pearle, Wendy, Rugg, Elizabeth
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