PERANGKAT LUNAK

2020 ◽  
Author(s):  
nadila shabira
Keyword(s):  
Image Processing ◽  
Computer System ◽  
Word Processing ◽  
The Other ◽  
Instruction Set ◽  
Daily Work ◽  
Processing Elements ◽  
Electronic Network ◽  
Input Processing ◽  
Software And Hardware

A computer system is an electronic network consisting of software and hardware that performs certain tasks (receiving input, processing input, storing commands, and providing output in the form of information). Besides that it can also be interpreted as elements that are related to carry out an activity using a computer. Computers can help humans in their daily work, jobs such as: word processing, number processing, and image processing. Elements of a computer system consist of human (brainware), software (software), instruction set (instruction set), and hardware (hardware). Thus these components are elements that are involved in a computer system. Of course hardware doesn't mean anything if there isn't one of the other two (software and brainware).

PERANGKAT LUNAK

2020 ◽  
Author(s):  
nadila shabira
Keyword(s):  
Image Processing ◽  
Computer System ◽  
Word Processing ◽  
The Other ◽  
Instruction Set ◽  
Daily Work ◽  
Processing Elements ◽  
Electronic Network ◽  
Input Processing ◽  
Software And Hardware

Abstract A computer system is an electronic network consisting of software and hardware that performs certain tasks (receiving input, processing input, storing commands, and providing output in the form of information). Besides that it can also be interpreted as elements that are related to carry out an activity using a computer. Computers can help humans in their daily work, jobs such as: word processing, number processing, and image processing. Elements of a computer system consist of human (brainware), software (software), instruction set (instruction set), and hardware (hardware). Thus these components are elements that are involved in a computer system. Of course hardware doesn't mean anything if there isn't one of the other two (software and brainware).

Perangkat lunak

2020 ◽  
Author(s):  
nadila shabira
Keyword(s):  
Image Processing ◽  
Computer System ◽  
Word Processing ◽  
The Other ◽  
Instruction Set ◽  
Daily Work ◽  
Processing Elements ◽  
Electronic Network ◽  
Input Processing ◽  
Software And Hardware

A computer system is an electronic network consisting of software and hardware that performs certain tasks (receiving input, processing input, storing commands, and providing output in the form of information). Besides that it can also be interpreted as elements that are related to carry out an activity using a computer. Computers can help humans in their daily work, jobs such as: word processing, number processing, and image processing. Elements of a computer system consist of human (brainware), software (software), instruction set (instruction set), and hardware (hardware). Thus these components are elements that are involved in a computer system. Of course hardware doesn't mean anything if there isn't one of the other two (software and brainware).

scholarly journals Sign Language Detection Using Image Processing

2021 ◽  
pp. 100-103
Author(s):  
Vinnayak Sharma ◽  
Khushbu Gupta ◽  
Dr. Krishna Singh
Keyword(s):  
Image Processing ◽  
Sign Language ◽  
Effective Means ◽  
Structural Features ◽  
The Other ◽  
Svm Classifier ◽  
Instruction Set ◽  
Language Detection

Sign language is an effective means of communication for the deaf and dumb. But those who cannot understand this language find it almost impossible to get a grip of what the other person is trying to communicate. The proposed research helps non-sign-language speakers in identifying gestures used in Sign Language. The methodology described in this paper is implemented using MATLAB. In this method, firstly, the signs are captured with the help of a webcam. The images captured are then processed further and the features are extracted from the captured images using different structural features. Comparison of the features is done using SVM Classifier can use this document as both an instruction set and as a template into which you can type your own text.

Efficient Computing in Image Processing and DSPs with ASIP Based Multiplier

2019 ◽  
Vol 13 (2) ◽  
pp. 174-180
Author(s):  
Poonam Sharma ◽  
Ashwani Kumar Dubey ◽  
Ayush Goyal
Keyword(s):  
Image Processing ◽  
High Speed ◽  
Computation Time ◽  
Digital Signal ◽  
Instruction Set ◽  
Computationally Efficient ◽  
Specific Instruction ◽  
Processor Core ◽  
Speed Performance ◽  
Application Specific

Background: With the growing demand of image processing and the use of Digital Signal Processors (DSP), the efficiency of the Multipliers and Accumulators has become a bottleneck to get through. We revised a few patents on an Application Specific Instruction Set Processor (ASIP), where the design considerations are proposed for application-specific computing in an efficient way to enhance the throughput. Objective: The study aims to develop and analyze a computationally efficient method to optimize the speed performance of MAC. Methods: The work presented here proposes the design of an Application Specific Instruction Set Processor, exploiting a Multiplier Accumulator integrated as the dedicated hardware. This MAC is optimized for high-speed performance and is the application-specific part of the processor; here it can be the DSP block of an image processor while a 16-bit Reduced Instruction Set Computer (RISC) processor core gives the flexibility to the design for any computing. The design was emulated on a Xilinx Field Programmable Gate Array (FPGA) and tested for various real-time computing. Results: The synthesis of the hardware logic on FPGA tools gave the operating frequencies of the legacy methods and the proposed method, the simulation of the logic verified the functionality. Conclusion: With the proposed method, a significant improvement of 16% increase in throughput has been observed for 256 steps iterations of multiplier and accumulators on an 8-bit sample data. Such an improvement can help in reducing the computation time in many digital signal processing applications where multiplication and addition are done iteratively.

Computer Vision and robotics in postal automation

1999 ◽  
Vol 18 (3-4) ◽  
pp. 265-273
Author(s):  
Giovanni B. Garibotto
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Pattern Recognition ◽  
Material Handling ◽  
State Of The Art ◽  
Short Description ◽  
The Other ◽  
Functional Requirements ◽  
Postal Automation ◽  
And Robotics

The paper is intended to provide an overview of advanced robotic technologies within the context of Postal Automation services. The main functional requirements of the application are briefly referred, as well as the state of the art and new emerging solutions. Image Processing and Pattern Recognition have always played a fundamental role in Address Interpretation and Mail sorting and the new challenging objective is now off-line handwritten cursive recognition, in order to be able to handle all kind of addresses in a uniform way. On the other hand, advanced electromechanical and robotic solutions are extremely important to solve the problems of mail storage, transportation and distribution, as well as for material handling and logistics. Finally a short description of new services of Postal Automation is referred, by considering new emerging services of hybrid mail and paper to electronic conversion.

scholarly journals Analysis of the Nosema Cells Identification for Microscopic Images

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3068
Author(s):  
Soumaya Dghim ◽  
Carlos M. Travieso-González ◽  
Radim Burget
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Image Processing ◽  
Deep Learning ◽  
The Other ◽  
Support Vector ◽  
Learning Approaches ◽  
Microscopic Images ◽  
Trained Neural Network ◽  
Nosema Disease

The use of image processing tools, machine learning, and deep learning approaches has become very useful and robust in recent years. This paper introduces the detection of the Nosema disease, which is considered to be one of the most economically significant diseases today. This work shows a solution for recognizing and identifying Nosema cells between the other existing objects in the microscopic image. Two main strategies are examined. The first strategy uses image processing tools to extract the most valuable information and features from the dataset of microscopic images. Then, machine learning methods are applied, such as a neural network (ANN) and support vector machine (SVM) for detecting and classifying the Nosema disease cells. The second strategy explores deep learning and transfers learning. Several approaches were examined, including a convolutional neural network (CNN) classifier and several methods of transfer learning (AlexNet, VGG-16 and VGG-19), which were fine-tuned and applied to the object sub-images in order to identify the Nosema images from the other object images. The best accuracy was reached by the VGG-16 pre-trained neural network with 96.25%.

A Model of Secure Functioning of Computer Systems

2021 ◽  
Vol 12 (3) ◽  
pp. 150-156
Author(s):  
A. V. Galatenko ◽  
◽  
V. A. Kuzovikhina ◽  
Keyword(s):  
Lower Bound ◽  
Computer System ◽  
Finite Automaton ◽  
Nonnegative Integer ◽  
The Other ◽  
Shannon Function ◽  
Security Breaches ◽  
System Functioning ◽  
The Cost ◽  
The Given

We propose an automata model of computer system security. A system is represented by a finite automaton with states partitioned into two subsets: "secure" and "insecure". System functioning is secure if the number of consecutive insecure states is not greater than some nonnegative integer k. This definition allows one to formally reflect responsiveness to security breaches. The number of all input sequences that preserve security for the given value of k is referred to as a k-secure language. We prove that if a language is k-secure for some natural and automaton V, then it is also k-secure for any 0 < k < k and some automaton V = V (k). Reduction of the value of k is performed at the cost of amplification of the number of states. On the other hand, for any non-negative integer k there exists a k-secure language that is not k"-secure for any natural k" > k. The problem of reconstruction of a k-secure language using a conditional experiment is split into two subcases. If the cardinality of an input alphabet is bound by some constant, then the order of Shannon function of experiment complexity is the same for al k; otherwise there emerges a lower bound of the order nk.

scholarly journals Virtual Table-Teleporter: Image Processing and Rendering for Horizontal Stereoscopic Display

2013 ◽  
Vol 12 (1) ◽  
pp. 30-43
Author(s):  
Bruno Eduardo Madeira ◽  
Luiz Velho
Keyword(s):  
The Other ◽  
Stereoscopic Display ◽  
Image Pair ◽  
Stereoscopic Image ◽  
Stereoscopic Video ◽  
Image Capture ◽  
Virtual Objects ◽  
Interactive Applications ◽  
Real Objects ◽  
Software And Hardware

We describe a new architecture composed of software and hardware for displaying stereoscopic images over a horizontal surface. It works as a ``Virtual Table and Teleporter'', in the sense that virtual objects depicted over a table have the appearance of real objects. This system can be used for visualization and interaction. We propose two basic configurations: the Virtual Table, consisting of a single display surface, and the Virtual Teleporter, consisting of a pair of tables for image capture and display. The Virtual Table displays either 3D computer generated images or previously captured stereoscopic video and can be used for interactive applications. The Virtual Teleporter captures and transmits stereoscopic video from one table to the other and can be used for telepresence applications. In both configurations the images are properly deformed and displayed for horizontal 3D stereo. In the Virtual Teleporter two cameras are pointed to the first table, capturing a stereoscopic image pair. These images are shown on the second table that is, in fact, a stereoscopic display positioned horizontally. Many applications can benefit from this technology such as virtual reality, games, teleconferencing, and distance learning. We present some interactive applications that we developed using this architecture.

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