This paper presents the first FPGA SoC implementation solution to the hand-written multi-digit numbers recognition problem. Our proposed solution employs a novel digit extraction method which relies on the identification of images\u27 non-zeros columns instead of the widely used computationally-expensive segmentation method. Digit prediction is performed by a multi-layer neural network. The paper presents a design and an FPGA implementation of the proposed solution; and also discusses various optimization techniques in the neural network implementation that lead to increased performance. Our proposed solution achieves a 96.76% detection accuracy and up to 2.47x speed-up in comparison to software solutions
The aim of this paper is to implement a Multilayer Perceptron (MLP) Neural Network to recognize and ...
Convolutional Neural Networks (CNNs) are the state-of-the-art in computer vision for different purpo...
This report documents the underlining theories and neural network that lead to the development of ha...
The goal of this work is the design and implementation of a low-cost system-on-FPGA for handwritten ...
This paper presents the design and implementation of a 2 layer feed-forward artificial neural networ...
This paper describes our implementation of a multilayer perceptron (MLP) learning network on a Cyclo...
Implementation of Deep Learning and Machine Learning Algorithms is always a challenge as they consum...
U okviru ovog rada opisana je implementacija sustava za prepoznavanje ručno pisanih znamenki u FPGA ...
This project uses Verilog to design and implement a neural network with region-of-interest (ROI) and...
The classification of handwritten digits through an analog feature extractor chip and neural classif...
Rozpoznawanie obrazów jest coraz szerzej wykorzystywanew branży informatycznej.Nieustannie rosnące r...
This paper presents a real-time hand gesture recognition system by accelerating a convolutional neur...
This paper explores the biomeric identification and verification of human subjects via fingerprints ...
Convolutional neural networks have been widely employed for image recognition applications because o...
In this paper we present a method for the recognition of handwritten digits and a practical implemen...
The aim of this paper is to implement a Multilayer Perceptron (MLP) Neural Network to recognize and ...
Convolutional Neural Networks (CNNs) are the state-of-the-art in computer vision for different purpo...
This report documents the underlining theories and neural network that lead to the development of ha...
The goal of this work is the design and implementation of a low-cost system-on-FPGA for handwritten ...
This paper presents the design and implementation of a 2 layer feed-forward artificial neural networ...
This paper describes our implementation of a multilayer perceptron (MLP) learning network on a Cyclo...
Implementation of Deep Learning and Machine Learning Algorithms is always a challenge as they consum...
U okviru ovog rada opisana je implementacija sustava za prepoznavanje ručno pisanih znamenki u FPGA ...
This project uses Verilog to design and implement a neural network with region-of-interest (ROI) and...
The classification of handwritten digits through an analog feature extractor chip and neural classif...
Rozpoznawanie obrazów jest coraz szerzej wykorzystywanew branży informatycznej.Nieustannie rosnące r...
This paper presents a real-time hand gesture recognition system by accelerating a convolutional neur...
This paper explores the biomeric identification and verification of human subjects via fingerprints ...
Convolutional neural networks have been widely employed for image recognition applications because o...
In this paper we present a method for the recognition of handwritten digits and a practical implemen...
The aim of this paper is to implement a Multilayer Perceptron (MLP) Neural Network to recognize and ...
Convolutional Neural Networks (CNNs) are the state-of-the-art in computer vision for different purpo...
This report documents the underlining theories and neural network that lead to the development of ha...