AGImageAI, developed by AlpineGate, is a cutting-edge image recognition software leveraging AI techniques to analyze various industries. AlpineGate, based in San Francisco, specializes in innovative solutions for image interpretation. Albert, the AI assistant, provides helpful information to users,

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Enable 2022 offers a comprehensive solution for making PowerBuilder applications multilingual, revolutionizing the way applications are localized. With advanced features like dynamic language switching and support for all languages, Enable Development is a leader in PowerBuilder outsourcing and mana

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Roboticists initially aimed for precise world modeling leading to perfect path planning and control concepts. However, imperfections in world models, control, and sensing called for a shift towards probabilistic methods in robot localization. This evolution from reactive to probabilistic robotics ha

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This research by the Tsinghua SUN Group introduces BIFROST, a novel approach that reinvents WiFi signals based on dispersion effect to enable precise indoor localization. The study addresses the challenge of limited line-of-sight (LoS) access points in indoor environments through Frequency and Spati

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SLAM (Simultaneous Localization and Mapping) is a concept crucial for robots to construct and update maps while tracking their own locations. It is likened to a chicken and egg problem, where building a map and localizing the robot occur concurrently. Hardware, landmarks, and steps involved in SLAM

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The media plays a significant role in shaping perceptions of body image, influencing how individuals view themselves and others. This article explores the impact of media portrayal on body image perceptions in both men and women, discussing the positive and negative influences of media representatio

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Understanding the process of image acquisition is crucial for digital image processing in GIS. It involves using physical devices sensitive to different energy bands to convert images into digital form through digitizers. Various methods such as single sensors, sensor strips, and sensor arrays are u

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Dental radiographs, though two-dimensional, can be limited in depicting depth and bucco-lingual relationships. Localization techniques like the right angle and tube-shift methods are used to accurately locate objects such as foreign bodies, impacted or unerupted teeth, and salivary stones within the

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The Deep Screen Image Crop and Enhance project, led by Aaron Ott and Amir Mazaheri, focuses on improving image quality through a multi-step approach involving image detection, cropping, and enhancement. The project utilizes advanced techniques like super-resolution networks and deep residual network

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U-Net is a convolutional neural network designed for image segmentation. It consists of a contracting path to capture context and an expanding path for precise localization. By concatenating high-resolution feature maps, U-Net efficiently handles information loss and maintains spatial details. The a

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Positron Emission Tomography (PET) is a medical imaging technique focusing on metabolic differences in the body. By using positron-emitting radioisotopes, PET can detect how molecules are taken up by healthy and cancerous cells, aiding in accurate tumor localization with lower doses. The evolution o

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The research presents PhantomPhantom, a system for protecting location privacy by leveraging physical layer cooperation. It explores the challenges of adversary localization systems and proposes solutions such as transmission power and frequency variations. The concept of creating ghost locations an

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The Microsoft Indoor Localization Competition 2018 in Porto brought together 34 teams to evaluate and compare technologies for indoor localization. The competition aimed to assess systems in 2D and 3D categories without the need for infrastructure deployment. Teams utilized LiDAR technology and were

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Explore the importance of data mapping for SDGs, utilizing the ADAPT tool to enhance localization and improve data planning. This tool assists in responding to global calls, assessing statistical capacity, and enhancing data system efficiency. Learn how ADAPT aids in identifying gaps, mapping data d

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Investigating how professional athletes utilize personal accounts as an image repair strategy after facing violations. The study delves into trends, variables affecting strategies, and the importance of public image for athletes. Key theoretical foundations include Image Restoration Theory and Accou

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The Fault Localization (Pinpoint) project proposal aims to pinpoint the exact source of failures within a cloud NFV networking environment by utilizing a set of algorithms and APIs. The proposal includes an overview of the fault localization process, an example scenario highlighting the need for fau

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Utilizing a novel self-learning semi-supervised technique with k-fold iterative training for cardiomegaly localization from chest X-ray images showed significant improvement in validation loss and labeled dataset size. The model, based on a VGG-16 backbone, outperformed traditional methods, resultin

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Explore the intricate world of neurology with a focus on brain localization, neuroaxis structures, and the distinctions between upper and lower motor neuron signs. Delve into the functions of brain lobes, brain stem anatomy, and spinal cord functions. Discover how upper motor neuron signs indicate l

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Delve into the world of localization and internationalization in ASP.NET Core, learning about the processes of customization for different languages and regions, key concepts like culture and locale, and practical examples of implementing i18n services and injecting localization support into control

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This research delves into potential biases affecting bug localization studies in software development. It explores misclassification of bug reports, pre-localized reports, and issues with ground truth files, shedding light on the challenges in accurately predicting and localizing software bugs.

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Bug localization is a crucial task in software maintenance. This paper introduces a novel approach using a convolutional neural network to learn unified features from bug reports in natural language and source code in programming language, capturing both lexicon and program structure semantics.

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The SLAM problem, a challenging task in mobile robotics, involves creating maps and determining a robot's pose in an unknown environment. Over time, researchers have made significant progress in solving this problem, dating back to the initial probabilistic methods for localization and mapping in 19

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Dive into Simultaneous Localization and Mapping (SLAM) technology used in autonomous race cars. Explore theoretical overviews, implementation methods like Extended Kalman Filter SLAM and Particle Filter SLAM, terms like scan matching and loop-closing, and popular implementations such as GMapping and

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Robot localization in a hallway is achieved through Kalman-like filters that use sensor data to estimate the robot's position based on a map of the environment. This process involves incorporating measurements, updating state estimates, and relying on Gaussian assumptions for accuracy. The robot's u

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This research explores the interconnectedness of country image, destination image, and Olympic Games image to identify beneficiaries and benefactors in these complex relationships. It aims to understand how these images influence each other and future visit intentions. The study utilizes a conceptua

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This content provides an overview of Internationalization (I18N), Globalization (G11N), and Localization (L10N) in ASP.NET MVC. It explains the processes involved in supporting different languages and regions, customizing applications, and the concepts of culture and locale.

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Delve into the realm of localization within mobile computing through two research threads, smartphone positioning systems, and enabling technology apps. Discover the sudden growth in the smartphone industry and the significance of location in applications, as envisioned by industry leaders. Uncover

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Two space projects, ExoMars and Sample Fetch Rover, are compared based on their Visual Localization algorithms. The study focuses on the timing performance, ease of use, and consistency with previous results of the GR740 processor. Visual Odometry and challenges like motion blur and lighting differe

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Utilizing contextual GAN, this project aims to automatically generate photographic images from hand-sketched objects. It addresses the challenge of aligning output with free-hand sketches while offering advantages like a unified network for sketch-image understanding. The process involves posing ima

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This study explores the alignment between theory and practice in the context of Spectrum-Based Fault Localization (SBFL). It delves into the analysis of execution traces, assigning suspiciousness scores to program elements, comparing SBFL formulas like Tarantula and Ochiai, and introducing new formu

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Software bug localization techniques like Tarantula focus on finding likely buggy code fragments in a software system by analyzing test results, code coverage, bug history, and code dependencies. The lack of an interface layer in existing techniques leads to handcrafted heuristics, posing a persiste

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Various fault localization techniques in software debugging are discussed, including black-box models, spectrum evaluation, comparison of artificial and real faults, failure modes, and design considerations. The importance of effective fault localization and improving fault localization tools is hig

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The Abstract Semi-Supervised Temporal Action Localization (SS-TAL) framework aims to enhance the generalization capability of action detectors using large-scale unlabeled videos. Despite recent progress, a significant challenge persists due to noisy pseudo-labels hindering efficient learning from ab

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Kookmin University's proposal focuses on the general architecture of PHY and MAC layers for image sensor communication. The document covers design principles, compatibility features, frame formats, error correction, and various considerations related to supporting commercial cameras, frame rates, sa

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SonicSurface 2.0 presents a cutting-edge approach to interactive smart mirrors using sound-based localization technology. By eliminating the need for expensive touch surfaces, this innovation offers a cost-effective and flexible alternative for a range of applications from games to smart home setups

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Indoor localization algorithms play a crucial role in determining the position of objects in indoor environments. Various methods such as GPS, TOA, TDOA, AOA, RSSI, and fingerprinting are employed for accurate localization. These algorithms measure factors like signal travel time, angle of arrival,

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This presentation delves into the intricacies of Neural Image Captioning, focusing on a model known as Neural Image Caption (NIC). The NIC's primary goal is to automatically generate descriptive English sentences for images. Leveraging the Encoder-Decoder structure, the NIC uses a deep CNN as the en

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This study presents a fast and efficient Material Point Method (MPM) solver for strain localization problems, introducing the Generalized Interpolation Material Point Method (GIMPM) and Convected Particle Domain Interpolation (CPDI). The MPM computational phase involves mapping, nodal solution, and

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This paper explores the localization of traffic at the edge network by major content providers, its impact on user performance, and the methodology to measure traffic locality. Using data from the University of Oregon, the study identifies top content providers such as Netflix and Akamai while inves

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Project CANTILO focuses on developing a 5G campus network in millimeter frequencies with TSN integration and precise localization services. It aims to leverage the unique characteristics of 5G, such as millimeter wave technology, for industrial applications. The project involves channel modeling, ne

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