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Journal articles on the topic 'Custom Objects'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

García-Ruiz, Pablo, Francisco J. Romero-Ramirez, Rafael Muñoz-Salinas, Manuel J. Marín-Jiménez, and Rafael Medina-Carnicer. "Fiducial Objects: Custom Design and Evaluation." Sensors 23, no. 24 (2023): 9649. http://dx.doi.org/10.3390/s23249649.

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Camera pose estimation is vital in fields like robotics, medical imaging, and augmented reality. Fiducial markers, specifically ArUco and Apriltag, are preferred for their efficiency. However, their accuracy and viewing angle are limited when used as single markers. Custom fiducial objects have been developed to address these limitations by attaching markers to 3D objects, enhancing visibility from multiple viewpoints and improving precision. Existing methods mainly use square markers on non-square object faces, leading to inefficient space use. This paper introduces a novel approach for creat

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Mtasher, Ashwaq Katham, and Esraa Hassan Jawad Al-wakel. "Custom Object Detection Using Transfer Learning with Pretrained Models for Improved Detection Techniques." Journal La Multiapp 5, no. 1 (2024): 10–18. http://dx.doi.org/10.37899/journallamultiapp.v5i1.843.

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Custom object detection plays a vital role in computer vision applications. However, developing an accurate and efficient custom object detector requires a substantial amount of labeled training data and significant computational resources. In this research, we propose a custom object detection framework that leverages transfer learning with pre-trained models to improve detection tech-niques.The framework first utilizes a pre-trained deep learning model, such as ResNet or VGGNet, as a feature extractor. The pre-trained model is trained on a large-scale dataset, enabling it to learn high-level

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Kumar, Aayush, Amit Kumar, Avanish Chandra, and Indira Adak. "Custom Object Detection and Analysis in Real Time: YOLOv4." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 3982–90. http://dx.doi.org/10.22214/ijraset.2022.43303.

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Abstract: Object recognition is one of the most basic and complex problems in computer vision, which seeks to locate object instances from the enormous categories of already defined and readily available natural images. The object detection method aims to recognize all the objects or entities in the given picture and determine the categories and position information to achieve machine vision understanding. Several tactics have been put forward to solve this problem, which is more or less inspired by the principles based on Open Source Computer Vision Library (OpenCV) and Deep Learning. Some ar

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Achirei, Stefan-Daniel, Razvan Mocanu, Alexandru-Tudor Popovici, and Constantin-Catalin Dosoftei. "Model-Predictive Control for Omnidirectional Mobile Robots in Logistic Environments Based on Object Detection Using CNNs." Sensors 23, no. 11 (2023): 4992. http://dx.doi.org/10.3390/s23114992.

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Object detection is an essential component of autonomous mobile robotic systems, enabling robots to understand and interact with the environment. Object detection and recognition have made significant progress using convolutional neural networks (CNNs). Widely used in autonomous mobile robot applications, CNNs can quickly identify complicated image patterns, such as objects in a logistic environment. Integration of environment perception algorithms and motion control algorithms is a topic subjected to significant research. On the one hand, this paper presents an object detector to better under

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Haokip, M. Hemminlal, and Ngamkholen Haokip. "Re-interpreting the traditional Semiotic Culture of ChinKuki-Mizo." International Journal of Humanities and Social Science Invention 14, no. 3 (2025): 91–96. https://doi.org/10.35629/7722-14039196.

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The Chin-Kuki-Mizos have various symbolisms representing ideas or characters, attributing them to natural objects or facts in their culture. The Chin-Kuki-Mizos are the ethnic group that has traced its origin to a mythological cave and are currently settled in different countries: Bangladesh, Myanmar and India. The rich customs and culture regarding signs, meanings and concepts are bound to their art and crafts. The Chin-KukiMizos have specific customs, symbols, and signs to convey good and bad messages. All the interpretations, beliefs and superstitions are related to their social, economic,

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Said, Yahia, Mohamed Atri, Marwan Ali Albahar, Ahmed Ben Atitallah, and Yazan Ahmad Alsariera. "Indoor Signs Detection for Visually Impaired People: Navigation Assistance Based on a Lightweight Anchor-Free Object Detector." International Journal of Environmental Research and Public Health 20, no. 6 (2023): 5011. http://dx.doi.org/10.3390/ijerph20065011.

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Facilitating the navigation of visually impaired people in indoor environments requires detecting indicating signs and informing them. In this paper, we proposed an indoor sign detection based on a lightweight anchor-free object detection model called FAM-centerNet. The baseline model of this work is the centerNet, which is an anchor-free object detection model with high performance and low computation complexity. A Foreground Attention Module (FAM) was introduced to extract target objects in real scenes with complex backgrounds. This module segments the foreground to extract relevant features

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Uličná, Lenka. "Disposed or Concealed: The Intriguing Case of Genizah Shoes." Ars Judaica 19, no. 1 (2023): 93–108. http://dx.doi.org/10.3828/arsjudaica.2023.19.8.

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Central European genizot, protected and closed spaces, usually in a synagogue attic, were for centuries used by local communities as a storage area for worn-out ritual objects, especially textual relics. However, beside the expected objects requiring genizah according to halakhah, genizot also contain objects that have no obvious connection to religion. Most remarkable is the abundance of shoes of various types and materials. These may have belonged to the deceased and as such, according to Jewish custom, should not be worn by anyone else. The practice of setting aside shoes, however, may have

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Jayakumar, Dontabhaktuni, and Samineni Peddakrishna. "Performance Evaluation of YOLOv5-based Custom Object Detection Model for Campus-Specific Scenario." International Journal of Experimental Research and Review 38 (April 30, 2024): 46–60. http://dx.doi.org/10.52756/ijerr.2024.v38.005.

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This study evaluates the performance of a custom object detection model based on the YOLOv5 architecture, specifically tailored for autonomous electric vehicles. The model undergoes pre-processing using the Roboflow computer vision platform, which offers a wide range of tools for data pre-processing and model training. The experiments were conducted on a diverse dataset comprising various objects encountered in campus-specific driving scenarios, such as pedestrians, vehicles, buildings, and obstacles. The performance of the custom object detection model is assessed using standard metrics, incl

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Sankar, Krishnakumar, Shantanu Patil, and Sridhar Krishnamurthy. "Analysis of grip and pinch strength using inverse dynamics simulation technique." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 232, no. 11 (2018): 1063–70. http://dx.doi.org/10.1177/0954411918798400.

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Grip strength is the function of musculotendinous action across the finger joints and varies while dealing objects of varying size and shape. Increasing object size requires greater effort by the fingers to grip. The main objective of this study is to analyse the variation in grip and pinch strength exerted on objects of various sizes and shapes in a short span of time. OpenSim 3.3 is open-source musculoskeletal modelling software used for performing simulations in a dynamic environment. The generic wrist model in OpenSim has movements on index finger and thumb only, for study purpose. Objects

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Reddy, Shiva Shankar, Venkata Rama Maheswara Rao, Priyadarshini Voosala, and Silpa Nrusimhadri. "You only look once model-based object identification in computer vision." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 827. http://dx.doi.org/10.11591/ijai.v13.i1.pp827-838.

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<span lang="EN-US">You only look once version 4 (YOLOv4) is a deep-learning object detection algorithm. It is used to decrease parameters and simplify network structures, making it suited for mobile and embedded device development. The YOLO detector can foresee an object's Class, bounding box, and probability of that Object's Class being found inside that bounding box. A probability value for each bounding box represents the likelihood of a given item class in that bounding box. Global features, channel attention, and special attention are also applied to extract more compelling informat

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Shankar, Reddy Shiva, Rao Venkata Rama Maheswara, Priyadarshini Voosala, and Silpa Nrusimhadri. "You only look once model-based object identification in computer vision." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 1 (2024): 827–38. https://doi.org/10.11591/ijai.v13.i1.pp827-838.

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You only look once version 4 (YOLOv4) is a deep-learning object detection algorithm. It is used to decrease parameters and simplify network structures, making it suited for mobile and embedded device development. The YOLO detector can foresee an object's Class, bounding box, and probability of that Object's Class being found inside that bounding box. A probability value for each bounding box represents the likelihood of a given item class in that bounding box. Global features, channel attention, and special attention are also applied to extract more compelling information. Finally, the model c

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Firman, Firman, Helfy Susilawati, Arief Suryadi Setyawan, and Mokh Mirza Etnisa Haqiqi. "Custom LiDAR Dataset for 3D Object Recognition in Restricted Spaces Using Voxel-RCNN." MDP Student Conference 4, no. 1 (2025): 425–30. https://doi.org/10.35957/mdp-sc.v4i1.11209.

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Autonomous vehicles play a crucial role in logistics, agriculture, and warehousing, requiring precise object detection and recognition for safe navigation in confined spaces. Traditional 2D sensor-based methods and simple LiDAR applications often struggle with depth perception and classification accuracy, limiting real-time decision-making. This study addresses these challenges by developing a custom LiDAR-based dataset for object recognition within the Voxel-RCNN framework, focusing on six object categories to enhance recognition accuracy. The Voxel-RCNN model was trained on this custom datas

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Ravi, Niranjan, Sami Naqvi, and Mohamed El-Sharkawy. "BIoU: An Improved Bounding Box Regression for Object Detection." Journal of Low Power Electronics and Applications 12, no. 4 (2022): 51. http://dx.doi.org/10.3390/jlpea12040051.

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Object detection is a predominant challenge in computer vision and image processing to detect instances of objects of various classes within an image or video. Recently, a new domain of vehicular platforms, e-scooters, has been widely used across domestic and urban environments. The driving behavior of e-scooter users significantly differs from other vehicles on the road, and their interactions with pedestrians are also increasing. To ensure pedestrian safety and develop an efficient traffic monitoring system, a reliable object detection system for e-scooters is required. However, existing obj

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Heredia, Jorge David Figueroa, Hamdi Sahloul, and Jun Ota. "Teaching Mobile Robots Using Custom-Made Tools by a Semi-Direct Method." Journal of Robotics and Mechatronics 28, no. 2 (2016): 242–54. http://dx.doi.org/10.20965/jrm.2016.p0242.

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[abstFig src='/00280002/15.jpg' width=""300"" text='Teach grasping point by custom-made tool' ]We propose a method for conveying human knowledge to home and office assistance robots by teaching them how to perform the process of grasping objects with a custom-made tool. Specifically, we propose a semi-direct teaching method that respects the limitations of the hardware on the robot while utilizing human experience for intuitive teaching. We specify the information necessary for grasping objects through the generation of teaching data, which include the grasping force, relative position, and or

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Cmiel, Vratislav, Larisa Chmelikova, Inna Zumberg, and Martin Kralik. "A Novel Gesture-Based Control System for Fluorescence Volumetric Data in Virtual Reality." Sensors 21, no. 24 (2021): 8329. http://dx.doi.org/10.3390/s21248329.

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With the development of light microscopy, it is becoming increasingly easy to obtain detailed multicolor fluorescence volumetric data. The need for their appropriate visualization has become an integral part of fluorescence imaging. Virtual reality (VR) technology provides a new way of visualizing multidimensional image data or models so that the entire 3D structure can be intuitively observed, together with different object features or details on or within the object. With the need for imaging advanced volumetric data, demands for the control of virtual object properties are increasing; this

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Konakalla, Kiran. "Building an End-to-End Hiring Process in Salesforce: Automating Recruitment with Custom Objects, Approval Processes, and Lightning Components." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 10 (2024): 1–6. http://dx.doi.org/10.55041/ijsrem8820.

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The process of hiring employees involves numerous steps that can be complex and time-consuming for HR teams. In this paper, we explore how Salesforce can be customized to streamline the hiring process end to end, from the moment a candidate submits an application to the final approval and onboarding. Using custom objects, automation, and integrations within Salesforce, we will develop an efficient system to track interview stages, manage interviewer feedback, and automate approval processes, resulting in a smoother, more organized hiring process. The paper includes key custom fields, workflow

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Simovych, Oksana. "From Ladder and Thread to Heaven: The Symbolic Meaning of the Path in a Fragment of the Linguistic World Image." Linguistics, no. 2 (44) (2021): 38–52. http://dx.doi.org/10.12958/2227-2631-2021-2-44-38-52.

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This article «From Ladder and Thread to Heaven: The Symbolic Meaning of the Path in a Fragment of the Linguistic World Image» explores the problem of the analysis of folk customs. These customs could be verbalized both in folk texts and in dialects. The specifics of this study lie in the linguistic analysis of the symbols which are usually interpreted as folk customs and folk objects. However, the symbolism of the objects in national customs causes the development of a symbolic meaning of the respective word that defines these objects. In this way, many symbols in folk customs become verbal, a

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Aujeszky, Tamas, Georgios Korres, Mohamad Eid, and Farshad Khorrami. "Estimating Weight of Unknown Objects Using Active Thermography." Robotics 8, no. 4 (2019): 92. http://dx.doi.org/10.3390/robotics8040092.

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Successful manipulation of unknown objects requires an understanding of their physical properties. Infrared thermography has the potential to provide real-time, contactless material characterization for unknown objects. In this paper, we propose an approach that utilizes active thermography and custom multi-channel neural networks to perform classification between samples and regression towards the density property. With the help of an off-the-shelf technology to estimate the volume of the object, the proposed approach is capable of estimating the weight of the unknown object. We show the effi

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Widyadara, Made Ayu Dusea, and Marga Asta Jaya Mulya. "Comparing YOLOv5 and YOLOv8 Performance in Vehicle License Plate Detection." International Journal of Research and Review 12, no. 2 (2025): 8–17. https://doi.org/10.52403/ijrr.20250202.

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The number of mobile vehicles on the roads in Indonesia is increasing every year. Therefore, it is essential to verify the identities of these vehicles for a variety of reasons, including locating stolen vehicles, enforcing traffic laws, managing car parks, and collecting tolls. Nevertheless, inspecting these vast numbers of vehicles manually is a challenging task. Motor vehicle number plate detection and recognition play a crucial role in intelligent transport systems. Generally, the detection and recognition of number plates on motor vehicles entail three main stages. Machine learning-based

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Rao Ulisi, Uma Maheswara. "Overview of Cloud-Based Custom Objects in ERP Cloud Implementation." International Journal of Scientific Research and Engineering Trends 11, no. 2 (2025): 1426–29. https://doi.org/10.61137/ijsret.vol.11.issue2.236.

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Kumail, Saifuddin Saif. "FI Custom Code block Extension in SAP S/4 HANA Finance." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 9, no. 6 (2021): 1–6. https://doi.org/10.5281/zenodo.14593179.

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To accommodate additional custom fields or reporting requirements, it is necessary to extend the Universal Journal with custom code blocks, ensuring all business-specific data is captured and available for analysis. There are two ways to extend code blocks. The Classic method is using the OXK3 transaction and the CI_COBL structure. The other method is using the Custom FieldsFiori app. Furthermore, you can use custom fields along with predefined business scenarios so that all involved business objects are extended, and values are passed along automatically.

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Datti, Jyothsna, and Ramesh Chandra Gollapudi. "Three-Dimensional Object Detection in Point Clouds with Multi-Stage Proposal Refinement Network." Journal of Robotics and Control (JRC) 6, no. 2 (2025): 745–56. https://doi.org/10.18196/jrc.v6i2.25602.

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Three-dimensional object detection in point clouds serves a vital role in autonomous driving and robotics. Point Clouds provide a vivid representation of 3D data that enables reliable object detection by acquiring the spatial distribution of points in a scene, facilitating the localization and identification of the objects within three-dimensional space. Precise localization of the objects remains challenging, particularly for moderately visible objects which attributes to inconsistent quality proposals. To tackle this, this paper presents a multi-stage proposal refinement network to generate

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King, Oliver R. T., Leigh N. Fletcher, Jake Harkett, Michael T. Roman, and Henrik Melin. "Custom JWST NIRSpec/IFU and MIRI/MRS Data Reduction Pipelines for Solar System Targets." Research Notes of the AAS 7, no. 10 (2023): 223. http://dx.doi.org/10.3847/2515-5172/ad045f.

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Abstract We present custom JWST data reduction pipelines for JWST NIRSpec/IFU and MIRI/MRS observations of solar system objects. The pipelines simplify the process of reducing the JWST observations, and include custom steps to significantly improve the data quality. Our custom processing routines include a “desaturation” routine to reduce the effect of saturation while still maintaining high signal-to-noise ratio, and custom flat field correction code to remove the significant artifacts found in MIRI/MRS observations. The pipelines also automatically generate a series of quick look plots and a

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Daramouskas, Ioannis, Dimitrios Meimetis, Niki Patrinopoulou, Vaios Lappas, Vassilios Kostopoulos, and Vaggelis Kapoulas. "Camera-Based Local and Global Target Detection, Tracking, and Localization Techniques for UAVs." Machines 11, no. 2 (2023): 315. http://dx.doi.org/10.3390/machines11020315.

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Multiple-object detection, localization, and tracking are desirable in many areas and applications, as the field of deep learning has developed and has drawn the attention of academics in computer vision, having a plethora of networks now achieving excellent accuracy in detecting multiple objects in an image. Tracking and localizing objects still remain difficult processes which require significant effort. This work describes an optical camera-based target detection, tracking, and localization solution for Unmanned Aerial Vehicles (UAVs). Based on the well-known network YOLOv4, a custom object

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Wu, Jie. "Enhancing Object Sorting Under Low-Light Conditions with CLAHE, Gaussian Blur, ROI, and Custom PID on a Raspberry Pi Robotic Arm." Applied and Computational Engineering 96, no. 1 (2024): 93–98. http://dx.doi.org/10.54254/2755-2721/96/20241240.

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Abstract. This paper addresses the significant challenge faced by robotic vision systems in detecting and sorting objects accurately under varying lighting conditions. Such variations in light can lead to decreased detection accuracy and inefficiencies in automated sorting processes. The paper employs a combination of literature review and experimental validation to investigate the effectiveness of advanced image processing techniques and control algorithms. Specifically, it explores the application of CLAHE adaptive compensation, Gaussian Blur, custom ROI, and PID controllers within a visual

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Erdenebat, Munkh-Uchral, Tuvshinjargal Amgalan, Anar Khuderchuluun, et al. "Comprehensive High-Quality Three-Dimensional Display System Based on a Simplified Light-Field Image Acquisition Method and a Full-Connected Deep Neural Network." Sensors 23, no. 14 (2023): 6245. http://dx.doi.org/10.3390/s23146245.

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We propose a high-quality, three-dimensional display system based on a simplified light field image acquisition method, and a custom-trained full-connected deep neural network is proposed. The ultimate goal of the proposed system is to acquire and reconstruct the light field images with possibly the most elevated quality from the real-world objects in a general environment. A simplified light field image acquisition method acquires the three-dimensional information of natural objects in a simple way, with high-resolution/high-quality like multicamera-based methods. We trained a full-connected

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Liu, Zhiguo, Enzheng Zhang, Qian Ding, Weijie Liao, and Zixiang Wu. "An Improved Method for Enhancing the Accuracy and Speed of Dynamic Object Detection Based on YOLOv8s." Sensors 25, no. 1 (2024): 85. https://doi.org/10.3390/s25010085.

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Accurate detection and tracking of dynamic objects are critical for enabling skill demonstration and effective skill generalization in robotic skill learning and application scenarios. To further improve the detection accuracy and tracking speed of the YOLOv8s model in dynamic object tracking tasks, this paper proposes a method to enhance both detection precision and speed based on YOLOv8s architecture. Specifically, a Focused Linear Attention mechanism is introduced into the YOLOv8s backbone network to enhance dynamic object detection accuracy, while the Ghost module is incorporated into the

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Pandey, Shweta. "Leveraging Workday for Effective Covid-19 Vaccination Tracking: Integrating Custom Objects and Security Features in Human Capital Management Systems." International Journal of Business Quantitative Economics and Applied Management Research 7, no. 1 (2021): 56–63. https://doi.org/10.5281/zenodo.14176000.

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Employee workforce is an asset to the organization, forming the foundation of every successful business. Effective Human Resource (HR) management is crucial in ensuring employees feel safe, valued, and properly supported. The HR department is responsible for maintaining employee safety, health, and satisfaction. In the wake of the COVID-19 pandemic, as companies plan to bring their workforce back to the office and covid vaccination tracking under state and federal mandates, it is critical to track employees' COVID-19 vaccination status in the Human Capital Management (HCM) system to ensure wor

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Yusardi, Rahmanditto Yusardi,, and M. Nasrul Kamal. "Perancangan Magazine Motor Custom di Kota Padang." DEKAVE : Jurnal Desain Komunikasi Visual 11, no. 1 (2021): 62. http://dx.doi.org/10.24036/dekave.v11i1.112334.

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Custom motorcycle was born to adapt to a builder and owner's will on character, shape, idea, and imagination. The custom culture is a primary part of a custom motorcycle. Printed media such as magazine plays an active role in developing custom culture in Padang. Magazine becomes a source of information capturing history on years and objects which are used as content. This magazine contains specifications and descriptions from some custom motorcycle's owners. With macro and micro photography techniques, the information is expected to be easily understood. The purpose of this design is to provid

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Jia, Yin, Balakrishnan Ramalingam, Rajesh Elara Mohan, Zhenyuan Yang, Zimou Zeng, and Prabakaran Veerajagadheswar. "Deep-Learning-Based Context-Aware Multi-Level Information Fusion Systems for Indoor Mobile Robots Safe Navigation." Sensors 23, no. 4 (2023): 2337. http://dx.doi.org/10.3390/s23042337.

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Hazardous object detection (escalators, stairs, glass doors, etc.) and avoidance are critical functional safety modules for autonomous mobile cleaning robots. Conventional object detectors have less accuracy for detecting low-feature hazardous objects and have miss detection, and the false classification ratio is high when the object is under occlusion. Miss detection or false classification of hazardous objects poses an operational safety issue for mobile robots. This work presents a deep-learning-based context-aware multi-level information fusion framework for autonomous mobile cleaning robo

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Lyu, Shijie. "UAV Image Object Detection Based on Attention Mechanism and Dilated Convolution." Applied and Computational Engineering 173, no. 1 (2025): 15–21. https://doi.org/10.54254/2755-2721/2025.24679.

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Existing algorithms for unmanned aerial vehicle (UAV) image object detection often face challenges such as low detection accuracy for small objects and missed detections of multi-scale objects. To address these issues, this paper proposes a UAV image object detection algorithm that integrates a channel attention mechanism with parallel-structured dilated convolution feature fusion. To enhance the algorithms feature representation capabilities in terms of channel attention and receptive field, the ResNet50 backbone is redesigned by incorporating the Squeeze-and-Excitation Network (SENet) and a

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Li, Kaylee Yaxuan, Yasha Iravantchi, Yichen Zhu, Hyunmin Park, and Alanson P. Sample. "HandSAW: Wearable Hand-based Event Recognition via On-Body Surface Acoustic Waves." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 9, no. 1 (2025): 1–29. https://doi.org/10.1145/3712276.

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Enabling computing systems to detect the objects that people hold and interact with provides valuable contextual information that has the potential to support a wide variety of mobile applications. However, existing approaches either directly instrument users' hands, which can reduce tactile sensation, or are limited in the types of objects and interactions they can detect. This work introduces HandSAW, a wireless wrist-worn device incorporating a Surface Acoustic Wave (SAW) sensor with enhanced bandwidth and signal-to-noise ratio while rejecting through-air sounds. The device features a seale

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Baran, Bartłomiej, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, and Tomasz Rymarczyk. "Ultrasound tomography enhancement by signal feature extraction with modular machine learning method." PLOS ONE 19, no. 1 (2024): e0297496. http://dx.doi.org/10.1371/journal.pone.0297496.

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Robust and reliable diagnostic methods are desired in various types of industries. This article presents a novel approach to object detection in industrial or general ultrasound tomography. The key idea is to analyze the time-dependent ultrasonic signal recorded by three independent transducers of an experimental system. It focuses on finding common or related characteristics of these signals using custom-designed deep neural network models. In principle, models use convolution layers to extract common features of signals, which are passed to dense layers responsible for predicting the number

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Azurmendi, Iker, Ekaitz Zulueta, Jose Manuel Lopez-Guede, and Manuel González. "Simultaneous Object Detection and Distance Estimation for Indoor Autonomous Vehicles." Electronics 12, no. 23 (2023): 4719. http://dx.doi.org/10.3390/electronics12234719.

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Object detection is an essential and impactful technology in various fields due to its ability to automatically locate and identify objects in images or videos. In addition, object-distance estimation is a fundamental problem in 3D vision and scene perception. In this paper, we propose a simultaneous object-detection and distance-estimation algorithm based on YOLOv5 for obstacle detection in indoor autonomous vehicles. This method estimates the distances to the desired obstacles using a single monocular camera that does not require calibration. On the one hand, we train the algorithm with the

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Kiran, Konakalla. "Automated Commission Calculation and Sales Quota Management in Salesforce: A Code-Driven Approach for Sales Efficiency." European Journal of Advances in Engineering and Technology 7, no. 12 (2020): 125–27. https://doi.org/10.5281/zenodo.14006043.

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This paper presents an approach to developing a commission calculator within Salesforce, utilizing custom objects, fields, Apex code, and process automation. The solution is designed to streamline commission calculations based on various sales criteria and ensure secure and scalable data management. By leveraging Salesforce’s capabilities and incorporating custom code where necessary, this approach enhances accuracy, efficiency, and transparency in sales commission management. The paper explores the architecture, coding techniques, and process automations employed to achieve this, while

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coons, ginger “all-lower-case”, and Matt Ratto. "Grease pencils and the persistence of individuality in computationally produced custom objects." Design Studies 41 (November 2015): 126–36. http://dx.doi.org/10.1016/j.destud.2015.08.005.

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Sirisha, Ms Mamidi. "Automated Object Detection and Tracking for Construction Site Safety." International Journal for Research in Applied Science and Engineering Technology 12, no. 12 (2024): 23–29. https://doi.org/10.22214/ijraset.2024.65695.

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The construction industry is increasingly adopting digital solutions to enhance safety, efficiency, and productivity. This project leverages the YOLOv8 object detection model and ByteTrack algorithm to track and count objects on construction sites. The system enables automated monitoring of personnel, machinery, and safety equipment through video analysis, addressing critical challenges like occlusions and dynamic object interactions. A custom dataset tailored for construction environments ensures high accuracy in detecting safety-critical items, such as personal protective equipment (PPE). Th

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Tupelo-Schneck, Robert. "An Introduction to Cordra." Research Ideas and Outcomes 8 (October 12, 2022): e95966. https://doi.org/10.3897/rio.8.e95966.

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Cordra is a digital object server that can function as a key infrastructural piece in FAIR DO (findable, accessible, interoperable and reusable digital object) implementations. Cordra manages JSON records and payloads as typed digital objects identified by handles. Cordra is neither a database nor an indexer, but it integrates the two and provides a unified interface.Cordra is intended to support both quick prototyping as well as production systems.For prototyping, Cordra makes it easy to get up and running rapidly with a digital object server. A potential Cordra administrator can download Cor

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Jacoski, Claudio Alcides, and Lissandro Machado Hoffmeister. "Potential use of BIM for automated updating of building materials values." Brazilian Journal of Operations & Production Management 15, no. 1 (2018): 35–43. http://dx.doi.org/10.14488/bjopm.2018.v15.n1.a4.

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This study proposes an artifact motivated by improved assertiveness in building design budgets. Building Information Modeling (BIM), with the structure of the parametric objects created in a file format with the Industry Foundation Classes (IFC) extension, can provide the data for the object, facilitating the design's control and monitoring process. Through the adoption of the IFC standard in the creation of these objects, the exchange of information between the tools of different software providers becomes viable, allowing interoperability between systems. This is a desired situation in the c

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Zhang, Yunbo, and Tsz Ho Kwok. "An interactive product customization framework for freeform shapes." Rapid Prototyping Journal 23, no. 6 (2017): 1136–45. http://dx.doi.org/10.1108/rpj-08-2016-0129.

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Purpose The purpose of this paper is to establish new computer-aided-design (CAD) framework to design custom product that is fabricated additive manufacturing (AM), which can produce complex three-dimensional (3D) object without additional tool or fixture. Additive manufacturing (AM) enables the fabrication of three-dimensional (3D) objects with complex shapes without additional tools and refixturing. However, it is difficult for user to use traditional computer-aided design tools to design custom products. Design/methodology/approach In this paper, the authors presented a design system to hel

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Ding, Dong, Zhengrong Deng, and Rui Yang. "YOLO-TC: An Optimized Detection Model for Monitoring Safety-Critical Small Objects in Tower Crane Operations." Algorithms 18, no. 1 (2025): 27. https://doi.org/10.3390/a18010027.

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Ensuring operational safety within high-risk environments, such as construction sites, is paramount, especially for tower crane operations where distractions can lead to severe accidents. Despite existing behavioral monitoring approaches, the task of identifying small yet hazardous objects like mobile phones and cigarettes in real time remains a significant challenge in ensuring operator compliance and site safety. Traditional object detection models often fall short in crane operator cabins due to complex lighting conditions, cluttered backgrounds, and the small physical scale of target objec

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Eldefrawy, Mahmoud, Scott A. King, and Michael Starek. "Partial Scene Reconstruction for Close Range Photogrammetry Using Deep Learning Pipeline for Region Masking." Remote Sensing 14, no. 13 (2022): 3199. http://dx.doi.org/10.3390/rs14133199.

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3D reconstruction is a beneficial technique to generate 3D geometry of scenes or objects for various applications such as computer graphics, industrial construction, and civil engineering. There are several techniques to obtain the 3D geometry of an object. Close-range photogrammetry is an inexpensive, accessible approach to obtaining high-quality object reconstruction. However, state-of-the-art software systems need a stationary scene or a controlled environment (often a turntable setup with a black background), which can be a limiting factor for object scanning. This work presents a method t

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Young, J. S., S. R. Fox, and K. S. Anseth. "A Novel Device for Producing Three-Dimensional Objects." Journal of Manufacturing Science and Engineering 121, no. 3 (1999): 474–77. http://dx.doi.org/10.1115/1.2832705.

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This work describes a novel device for producing three-dimensional objects that has been developed using a liquid crystal display as a programmable, dynamic mask and visible light to initiate photopolymerization. This device has the potential to produce three-dimensional objects of comparable quality to the existing commercial devices, but in significantly less time. Additionally, capital, maintenance and operating costs are expected to be substantially lower than those for laser-based systems. The reduction in time and expense could expand this technology into the realm of custom part product

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Ebel, Henrik, and Peter Eberhard. "Cooperative transportation: realizing the promises of robotic networks using a tailored software/hardware architecture." at - Automatisierungstechnik 70, no. 4 (2022): 378–88. http://dx.doi.org/10.1515/auto-2021-0105.

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Abstract With cooperative transportation, the paper looks at a demanding problem from distributed robotics. At its heart, the proposed transportation scheme uses distributed model predictive control. Yet, distributed control alone does not suffice to solve the task. Thus, also distributed organization, a custom software architecture, simulation, and custom robotic hardware are dealt with, bridging the gap between distributed control theory and practical robotics. The robots are enabled to transport arbitrarily-shaped objects, automatically adapting to changing circumstances and numbers of robo

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Natuskar, Sakshi. "Voice Assistant for Blind." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 3956–60. https://doi.org/10.22214/ijraset.2025.69183.

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Navigating safely through everyday environments can be extremely challenging for people with visual impairments. To address this, we developed a smart Blind Voice Assistant that uses the YOLOv8 object detection model to identify surrounding objects in real time. The system can detect both common and potentially dangerous items, estimate their approximate distance in steps, and immediately inform the user through voice feedback. This approach allows users to become more aware of their surroundings and make safer decisions as they move around. By training the model with both standard COCO data a

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Calabrese, Bernardo, Ramiro Velázquez, Carolina Del-Valle-Soto, Roberto de Fazio, Nicola Ivan Giannoccaro, and Paolo Visconti. "Solar-Powered Deep Learning-Based Recognition System of Daily Used Objects and Human Faces for Assistance of the Visually Impaired." Energies 13, no. 22 (2020): 6104. http://dx.doi.org/10.3390/en13226104.

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This paper introduces a novel low-cost solar-powered wearable assistive technology (AT) device, whose aim is to provide continuous, real-time object recognition to ease the finding of the objects for visually impaired (VI) people in daily life. The system consists of three major components: a miniature low-cost camera, a system on module (SoM) computing unit, and an ultrasonic sensor. The first is worn on the user’s eyeglasses and acquires real-time video of the nearby space. The second is worn as a belt and runs deep learning-based methods and spatial algorithms which process the video coming

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PHADKE, Anuradha, Rucha VAIKAR, Avni KHETRAPAL, and Mehul VERMA. "Object Detection on Thermal Images: Performance of Yolov4 vs Yolov4 Tiny trained on Custom Datasets." Electrotehnica, Electronica, Automatica 72, no. 3 (2024): 53–61. http://dx.doi.org/10.46904/eea.23.72.3.1108006.

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The process of identifying and pinpointing the location of objects within an image or video is a crucial task in computer vision, known as object detection. While there has been significant progress in object detection using conventional optical RGB images, there has been comparatively less research done on object detection using thermal images. Thermal imaging has the advantage of being able to capture images in low light or even complete darkness, making it an attractive technology for surveillance applications. However, due to the scarcity of publicly available thermal image datasets, the d

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Han, Shaolong, Shangrong Wang, Wenqi Liu, YongQiang Gu, and Yujie Zhang. "Swarm Intelligence-Enhanced Detection of Small Objects Using Key Point-Driven YOLO." International Journal of Swarm Intelligence Research 16, no. 1 (2025): 1–20. https://doi.org/10.4018/ijsir.368649.

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Traditional object detection methods, such as anchor-based YOLO variants, face challenges due to the irregular shapes and small sizes of these contaminants. This paper introduces a novel approach that leverages swarm Intelligence to enhance the performance of a keypoint-driven YOLO framework. By integrating keypoint detection with Boundary-Aware Vectors (BBAVectors) and utilizing swarm intelligence algorithms for model optimization, our approach improves the localization and identification of small, irregularly shaped non-metallic objects. By optimizing the feature extraction process through s

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Jeong, Soo-Yeon, Junseok Kim, and Sun-Young Ihm. "The Design and Construction of a Grid Skyline for Custom-Built PC Recommendations Based on a Multi-Attribute Model." Designs 7, no. 5 (2023): 104. http://dx.doi.org/10.3390/designs7050104.

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In recent years, people have been buying custom-built PCs based on the performance they want and what they will use them for. However, there are many challenges for non-technical users when purchasing a custom-built PC. Not only is the terminology of computer devices unfamiliar to non-experts, but there are many specifications for different computer devices that need to be considered. Therefore, this paper proposes a method for recommending appropriate device models when purchasing custom-built PCs using a skyline. Because different computer devices have different specifications, we need a met

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Rey, Thomas, Julien Moras, Alexandre Eudes, and Antoine Manzanera. "Real-time visual pose estimation: from BOP objects to custom drone — A journey." Mechatronics 109 (August 2025): 103339. https://doi.org/10.1016/j.mechatronics.2025.103339.

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