COMPUTER VISION IEEE PAPER 2022



Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human visual system can do.
Computer vision goes under the names of CV or AI vision. It is a field of artificial intelligence that handles image and video analysis. Computer vision systems include a set of AI techniques. The latter allows a computer to have a human-like vision that extracts information from the visual world
Computer vision is a field of artificial intelligence that trains computers to interpret and understand the visual world. Using digital images from cameras and videos and deep learning models, machines can accurately identify and classify objects
Computer vision is used to detect and classify objects (e.g., road signs or traffic lights), create 3D maps or motion estimation, and played a key role in making autonomous vehicles a reality. Self-driving cars collect data on their surroundings from sensors and cameras, interpret it, and respond accordingly








Transfer Learning and its application in Computer Vision : A Review
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Computer Vision programs have been successful in achieving exceptional things with the use of Artificial Intelligence which prove to be a great benefit to society. Miraculous success

Computer Vision and Deep Learning for Fish Classification in Underwater Habitats: A Survey
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However, although DL, and its variants such as CNNs, have been applied to various applications across a multitude of domains [19 21], their use in conjunction with computer vision for In recent years, computer vision a non-contact and learning techniques to the computer vision algorithms is intelligence, imaging informatics, and computer vision . He holds two patents

Practical Considerations in Utilization of Computer Vision
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Unfortunately, the vast majority of surgical computer vision questions cannot be answered with this little data. Therefore, most computer vision groups will need to pursue de novo data

A Picture Is Worth a Thousand Features! Using Computer Vision Alongside Machine Learning in Computer Systems
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In this Section, I will showcase how computer vision can be used alongside machine learning in computer systems, focusing on a particular use case, that is to learn data access patterns

Extending design cognition with computer vision and generative deep learning
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This thesis proposes to scrutinize the project of extending cognition in the field of design by providing the exploration of alternative procedures of formalization. It aims at investigating

Detecting Spatial-temporal urban ponding distribution from surveillance videos based on computer vision
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the development of computer vision technology bring new opportunities for extracting ponding information from these image data. This study proposes a computer visionbased method

COMPUTER VISION AIDED ELECTRODE WEAR ESTIMATION IN ELECTRICAL DISCHARGE MACHINING PROCESS
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method using a computer vision technique. The computer . The electrode wear is estimated by means of the decrease of electrode length after EDM, accordingly computer vision aided

Formulation of Mathematical Model to Determine The Risk of Computer Vision Syndrome (VCS) in The Use of An Ergonomic Drawing Tablet Application in
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The use of computers in this present age is very widespread, as almost all human activities utilize computer technology to complete their tasks. With the aid of computers, completing

Porting Computer Vision Models to the Edge for Smart City Applications: Enabling Autonomous VisionBased Power Line Inspection at the Smart Grid Edge for
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the Icelandic smart grid operator, we apply convolutional neural networks for image processing to detect smart grid transmission infrastructure and modify the resulting computer vision (

Biomedical Applications of Computer Vision using Artificial Intelligence
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image processing and computer vision machine learning Computer vision is a field of computer science concerned with understanding images, videos, or 3D volumes by the computerNowadays, AI has been highly explored for computer vision applications . So, we use the face detection algorithms, to produce the computer systems the ability to find and recognize

Prevalence of Computer Vision Syndrome and Patterns of Electronic Devices Usage before and during COVID-19 Pandemic among Medical Students in
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to increased prevalence of Computer Vision Syndrome (CVS) visionrelated problems that result from prolonged computer are eye strain, headache, blurred vision dry eyes as well as

A hierarchical semantic segmentation framework for computer visionbased bridge damage detection
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Computer visionbased damage detection using remote cameras and unmanned aerial vehicles (UAVs) enables efficient and low-cost bridge health monitoring that reduces labor costs

Affiliation: Electrical and Computer Engineering, Carnegie Mellon University
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Abstract FreshEyes is a smart fridge attachment and interface system that tracks fresh produce using computer vision and AI. Our user-friendly and integrated system can be placed on

VisionGuided Laser Safety System
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Advancement in computer vision over the last decade or so has opened the door to new applications exploiting facial recognition and object detection that are being widely researched Machine learning techniques have always played an important and often central role in the development of computer vision algorithms. Computer vision in the 1970s grew out of the fields

Fast and Reliable VisionBased Navigation for Real Time Kinematic Applications
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computer vision applications, such as SLAM, vision based navigation, image registration, camera calibration, automatic image mosaic, indexing, recognizing panoramas, and traffic sign

Comparative analysis of Tesseract and Google Cloud Vision for Thai vehicle registration certificate.
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Computer vision uses deep learning to create neural networks that guide image processing and analysis [19]. Computer vision All available tools used in computer vision include belong to the field of Computer Vision . Computer vision is one of the most active research fields that lies at the intersection of deep learning and machine vision . This paper presents an

Improving Segmentation of the Inferior Alveolar Nerve through Deep Label Propagation
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segmentation of the IAN in CBCT scans, using classical computer vision methods at first [1 Classical computer vision methods are mostly based on Statistical Shape Model (SSM), and

Enhancing the Robustness of Visual Object Tracking via Style Transfer
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Abstract: The performance and accuracy of computer vision systems are affected by noise in In this paper, we have focused on the stability and robustness of one computer vision

NNLander-VeriF: A Neural Network Formal Verification Framework for VisionBased Autonomous Aircraft Landing
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vision visionbased systems with high performance, we argue that these models can be used for verification. In other words, we employ the philosophy of data-driven design of vision

ComputerAided Hierarchical Interactive Gesture Modeling Under Virtual Reality Environment
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In addition, aiming at the shortcomings of leap motion gesture tracking in desktop VR, we use computer vision technology and deep learning gesture recognition method to propose a

Development of a machine vision program to determine the completeness of wrapping plants in the soil
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use computer vision to study the color spectrum of citrus fruits to detect defects and diseases. They note that the color of the peel of oranges can indicate a number of dangerous

Journal of Nature and Spatial Sciences
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Computer vision approaches can be used to automatically identify and classify plant species. Modern approaches use deep learning in computer vision . Materials and methods: In this

Occupational health and postural discomfort faced by bankers due to computer usage
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To finish the work on computer they have to spend 6 to 8 of using a computer can increase the chance of vision related daily having high computer vision syndrome then those

Are deep CNNs faithful models of the visual system
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Additionally, by reinterpreting the original connection between human and computer vision early stages of vision most notably the retina, the first neuronal tissue responsible for vision .

Accident Detection Using ML and AI Techniques
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computer vision in detecting accidents from CCTV footage and alerting Rescue systems. Computer vision is With the assistance of Computer Vision technologies, organisations are

VisionBased UAV Distribution Line Inspection Using Deep Learning
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This network pushes the state of the art for mobile tailored computer vision models, by significantly decreasing the number of operations and memory needed while retaining the same

OPEN-SOURCE ROBOTIC PROCESS AUTOMATION A CASE STUDY WITH ROBOCORP
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Also, importantly, we highlight the creation and use of a computer vision module in the Robots which will be of interest to AI/ML scientists and users. The applications that were the target

Virtual and Augmented Reality
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Augmented Reality (AR) is highly dependent on computer vision (CV) methods, whether it is In Figure 1 we can see all of this approaches are applied to use Computer vision methods

Vi-Fi: Associating Moving Subjects across Vision and Wireless Sensors
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In Proceedings of the IEEE conference on computer vision and pattern recognition. 8427 In Proceedings of the IEEE conference on computer vision and pattern recognition. 7942 7951 This project aims to amalgamate computer vision and AR techniques to create a platform that has applications in several industries like retail, gaming, cosmetics, electronics

GESTURE RECOGNITION BASED VIRTUAL MOUSE AND KEYBOARD
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People are using this vision in many parts of daily life at Computer vision is employed in this research to create an optical mouse and keyboard that uses hand motions. The computers

Evaluation of a Local Descriptor for HDR Images
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Several computer vision applications rely on the usage of FPs. Most FP descriptors are designed to support low dynamic range (LDR) images as input. However, high dynamic range (

Non-Uniform Illumination and Low Light Image Enhancement Techniques: An Exhaustive Study
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It can be problematic for artificial intelligence, computer vision techniques and detection application’s artificial intelligence and computer vision techniques. The methods used for

Gorgeous Pixel Artwork Generation with VQGAN-CLIP
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While the impact of advances in computer vision with deep learning begins to permeate the business world outside the ML community, the presence of DL techniques in the art world

You Only Infer Once: Cross-Modal Meta-Transfer for Referring Video Object Segmentation
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In Proceedings of the IEEE conference on computer vision and IEEE international conference on computer vision 2961 2969 In Proceedings of the IEEE conference on computer vision

OpenSceneVLAD: Appearance Invariant, Open Set Scene Classification
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Scene classification is a well-established area of computer vision research that aims to classify a scene image into pre-defined categories such as playground, beach and airport.

Supplementary Material AdaFace: Quality Adaptive Margin for Face Recognition
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In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 212 2 2017. 2 Brianna Maze, Jocelyn Adams, James A Duncan, Nathan Kalka, Tim sing and computer vision in which vehicle classification is a critical domain. The purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and

Federated learning with uncertainty in medical problems
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Edge Detection is one of the fundamental problems in computer vision , where in recent research works traditional systems, have been outperfomed by Deep Learning models, such

Object Detection Based on Template Matching and SURF Algorithm
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Object Detection is one of the most important applications in the field of computer vision . Object detection algorithms generally use extracted features and learning algorithms for

Morphology Decoder: Untangling Heterogeneous Texture and Determining Permeability with Machine Learning 3D Vision
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3- We created a novel computer vision semantic segmentation representation, Controllable Measurable Volume CMV, guided with calibration models, to have a novel 3D image flow

A Review on Human Activity Recognition Techniques and Comparative Performance Analysis
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The techniques based on machine learning have been applied successfully in diverse fields ranging from pattern recognition, computer vision as well on spacecraft engineering, finance

Multi-stage RGB-based Transfer Learning Pipeline for Hand Activity Recognition
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is a challenging problem in computer vision that has attracted much attention due to its wide research and practical applications, such as Human- Computer Interaction (Sridhar et al.,

HARTIV: Human Activity Recognition Using Temporal Information in Videos
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Abstract: Nowadays, the most challenging and important problem of computer vision is to automatically identified using intelligence systems and computer vision technology. In a long

Hybrid Improved Models Combined SR3 Module for Animal Recognition in Electric Cars Actual Vision
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other vehicles’ assisted vision visual assistance for blind people, robot vision assistance, etc.

Reducing Flipping Errors in Deep Neural Networks
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Deep neural networks (DNNs) have been widely applied in various domains in artificial intelligence including computer vision and natural language processing. A DNN is typically

Configuration and Enablement of Vision Sensor Solutions Through a Combined Simulation Based Process Chain
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Machine vision solutions can perform within a wide range of applications and are commonly both configuration and enablement of machine vision systems is presented in this paper.

IMAGE COMPRESSION USING AI: BRIEF INSIGHTS INTO DEEP LEARNING TECHNIQUES AND AI FRAMEWORKS
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The Open Source Computer Vision (OpenCV) Library offers hundreds of machine learning and computer vision algorithms, with thousands of functions to support these algorithms. It isDeep learning became very popular in the computer vision field after late 201 when a won an overwhelming victory in the best-known computer vision competition, ImageNet [23]. The

SAMBHASHAN A Sign Language Recognizer and Convertor
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Sambhashan has its own dataset and to create a dataset we used open computer vision (OpenCV). OpenCV is an open source library used for real time computer vision . OpenCV are

Image-to-image Translation via Contour-consistency Networks
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With the progress of deep learning, several related areas of study have emerged, such as computer vision and speech recognition. In computer vision image-to-image translation is vital

WATER LEVEL FLUCTUATION USING SURVEILLANCE CAMERA
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Computer vision is one of the common approaches being employed which include the use of image segmentation techniques for image understanding and image analysis. The

Sim2Real Object-Centric Keypoint Detection and Description
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Keypoint detection and description play a central role in computer vision . Most existing methods are in the form of scene-level prediction, without returning the object classes of different

OBJECT RECOGNITION BY VISUALLY IMPAIRED USING MACHINE LEARNING: A STUDY
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It aims in development of computer programs which can access data and use those data to Industries have created a variety of computer vision products and services by developing

A Multilevel Deep Feature Selection Framework for Diabetic Retinopathy Image Classification
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(DR) which can cause a major loss of vision . The symptoms typically originate within the retinal Recently, Computer Vision (CV) with deep neural networks can train models with highComputer Vision algorithms are approaching human-level performance in visual perception tasks. From image classification to video analytics Computer Vision has Computer Vision

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