[PDF] Top 20 High Performance Scalable Deep Learning Accelerator Unit on FPGA
Has 10000 "High Performance Scalable Deep Learning Accelerator Unit on FPGA" found on our website. Below are the top 20 most common "High Performance Scalable Deep Learning Accelerator Unit on FPGA".
High Performance Scalable Deep Learning Accelerator Unit on FPGA
... Largescale deep learning neural network ...accelerating deep learning algorithms are Field-Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), and Graphic ... See full document
5
DLAU: A Scalable Deep Learning Accelerator Unit on FPGA
... the performance and cost of the DLAU accelerator, we have implemented the hardware prototype on the Xilinx Zynq Zedboard development board, which equips ARM Cortex-A9 processors clocked at 667 MHz and ... See full document
8
Ineffectual Neuron Free Deep Learning Accelerator
... good performance as well as computation. In supervised learning algorithms, CNN works as a feed forward process for training and ...have high computation ability for unprecedented accuracy on AI ... See full document
8
Efficient Deep Learning Hardware Accelerator Using Past Adder
... Machine Learning offers numerous creative applications in the IoT gadgets, for example, face acknowledgment, keen security and article identification ...handling unit (GPU's) ground-breaking calculation ... See full document
6
Acceleration of Deep Learning on FPGA
... for high throughput and modern GPUs can achieve thousands of floating point operations per second ...GPU accelerator from Nvidia is able to compute more than four thousands of single precision floating ... See full document
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Scalable Packet Classification on FPGA
... develop scalable solutions for advanced packet classification which is having higher performance, supports large rule sets as well as more packet header ...Kintex-7 FPGA development board with Xilinx ... See full document
8
Advanced Machine Learning Approach: Deep Learning
... Abstract:- Deep learning can say a set of AI (AI) machine learning networks that can learn from unstructured or unlabeled ...faces. Deep Learning is associated AI performing that ... See full document
5
Design of Image Recognition Accelerator Based on FPGA
... The traditional CNN consists of a convolutional layer, a pooled layer, a fully connected layer, an activation functionlayer, and Softmax and loss layers. This paper designs a custom network structure file that can reduce ... See full document
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FPGA-based Fault-injection and Data Acquisition of Self-repairing Spiking Neural Network Hardware
... multiple FPGA-based acquisition platforms in the ...an FPGA as a bridge between an Analogue to Digital Converter (ADC) and an off-chip DDR3 SDRAM ...6 FPGA for acquiring data from an ADC and sending ... See full document
6
High performance vegetable classification from images based on AlexNet deep learning model
... Abstract: Deep learning techniques can automatically learn features from a large number of image data ...a high performance method for vegetable images classification based on deep ... See full document
7
SCALABLE HIGH PERFORMANCE MULTIDIMENSIONAL SCALING
... as high-performance computing, database, and machine learning and data mining communities, to learn how to deal with such large and high dimensional data in this data deluged ... See full document
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Design and implementation of FPGA based DNA sequence alignment accelerator
... processing unit holds a character from the query ...the unit are compared, if they are identical, the logic ‘1’ would be generated and otherwise, and the logic ‘0’ would be ...processing unit in the ... See full document
36
SOLAR: Scalable Online Learning Algorithms for Ranking
... First of all, among all the algorithms, we found that both SOLAR-I and SOLAR-II achieve sig- nificantly better performance than Prank, which proves the efficacy of the proposed pairwise al- gorithms. Second, we ... See full document
10
Motivational profiles of medical students: Association with study effort, academic performance and exhaustion
... study, performance in medical school and preference of specialty ...more deep learning [15,16], higher achievement [17,18], enhanced well-being or adjustment [19,20], decreased drop-out intention and ... See full document
8
Human Face Detection and Identification using Deep Metric Learning
... In the equation 2, Zi represents the new feature vector of lower dimensional space. Negative aspect of this method, it tries to max inter and intra class scattering. Inter class scattering is good for classification ... See full document
8
Using CNN and HOG Classifier to Improve Facial Expression Recognition
... a deep learning algorithm with ability to take an image and learn weight and biases given to it, and make differentiation of one aspect to ...unsupervised learning algorithms, whereby each neuron ... See full document
5
Scalable High Performance Dimension Reduction
... To deal with even more points, like millions of data, which is not eligible to run normal MDS algorithm in cluster systems. Also, I will investigate and analyze how weight values[r] ... See full document
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FPGA Implementation of Machine Learning Hardware Accelerator for Mobile Applications of Brain Computer Interface
... have high requirements on power consumption, size and speed, thus how to customize hardware accelerators that meets practical requirements is current research ...machine learning algorithms in BCI, and ... See full document
7
Scalable High Performance Dimension Reduction
... Seung-Hee Bae, Jong Youl Choi, Judy Qiu, Geoffrey Fox. Dimension Reduction Visualization of Large High-dimensional Data via Interpolation. in the Proceedings of The ACM International Symposium on High ... See full document
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Exploiting Structure for Scalable and Robust Deep Learning
... of-the-art performance in a wide range of computer vision tasks, such as visual recognition Krizhevsky, Sutskever, and Hinton, 2012; Christian Szegedy, Liu, et ...including deep neural ... See full document
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