Relevant bibliographies by topics / Camera-AI method

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Camera-AI method'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Camera-AI method"

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Kafetzis, Ioannis, Philipp Sodmann, Robert Hüneburg, et al. "Advancing artificial intelligence applicability in endoscopy through source-agnostic camera signal extraction from endoscopic images." PLOS One 20, no. 6 (2025): e0325987. https://doi.org/10.1371/journal.pone.0325987.

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Introduction Successful application of artificial intelligence (AI) in endoscopy requires effective image processing. Yet, the plethora of sources for endoscopic images, such as different processor-endoscope combinations or capsule endoscopy devices, results in images that vastly differ in appearance. These differences hinder the generalizability of AI models in endoscopy. Methods We developed an AI-based method for extracting the camera signal from raw endoscopic images in a source-agnostic manner. Additionally, we created a diverse dataset of standardized endoscopic images, named Endoscopic
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Murai, Yasuyuki, Hisayuki Tatsumi, Yumiko Ota, and Masahiro Miyakawa. "Prototype of a Method to Support the Walking of Visually Impaired by Detecting the Walkable Area Using Pedestrians." International Journal of Engineering and Technology 15, no. 2 (2023): 41–44. http://dx.doi.org/10.7763/ijet.2023.v15.1217.

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The goal of this study is to support the walking of visually impaired people using AI and a small camera. It is difficult for the visually impaired to walk straight toward the target due to the characteristics of the disability. Even if they think they are walking straight, they will move off to the left and right. For this reason, they may have an accident such as falling from the platform of the train. In this report, in order to enable visually impaired people to walk safely toward the target, a small camera attached to the body captures the direction of travel, detects the area where the p
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song, LiuQing, and Amir Ali Mokhtarzadeh. "Research on automatic charging method based on quadruped robot." Journal of Physics: Conference Series 2467, no. 1 (2023): 012028. http://dx.doi.org/10.1088/1742-6596/2467/1/012028.

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Abstract The problem of automatic charging of quadruped robots has been studied for a long time, but in the docking process, the success rate of robot docking is low. This paper proposes a kind of module based on the infrared tube module, laser ranging sensor group module, wireless communication module, charging station control unit module, and the automatic charging module, which includes two-dimensional code, voltage sensor group module, servo motor module, robot control unit module, serial communication module, and AI vision camera module. The docking method of combining the automatic charg
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Tomić, Martina, Romano Vrabec, Đurđica Hendelja, Vilma Kolarić, Tomislav Bulum, and Dario Rahelić. "Diagnostic Accuracy of Hand-Held Fundus Camera and Artificial Intelligence in Diabetic Retinopathy Screening." Biomedicines 12, no. 1 (2023): 34. http://dx.doi.org/10.3390/biomedicines12010034.

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Our study aimed to assess the role of a hand-held fundus camera and artificial intelligence (AI)-based grading system in diabetic retinopathy (DR) screening and determine its diagnostic accuracy in detecting DR compared with clinical examination and a standard fundus camera. This cross-sectional instrument validation study, as a part of the International Diabetes Federation (IDF) Diabetic Retinopathy Screening Project, included 160 patients (320 eyes) with type 2 diabetes (T2DM). After the standard indirect slit-lamp fundoscopy, each patient first underwent fundus photography with a standard 4
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Göncz, Levente, and András László Majdik. "Object-Based Change Detection Algorithm with a Spatial AI Stereo Camera." Sensors 22, no. 17 (2022): 6342. http://dx.doi.org/10.3390/s22176342.

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This paper presents a real-time object-based 3D change detection method that is built around the concept of semantic object maps. The algorithm is able to maintain an object-oriented metric-semantic map of the environment and can detect object-level changes between consecutive patrol routes. The proposed 3D change detection method exploits the capabilities of the novel ZED 2 stereo camera, which integrates stereo vision and artificial intelligence (AI) to enable the development of spatial AI applications. To design the change detection algorithm and set its parameters, an extensive evaluation
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Ishiguro, Minoru, Yotsumi Yoshii, Toshimasa Chaki, and Keigo Kasaya. "An Easy Snowpack Depth Evaluation Using Smartphone, Bluetooth Device, and Augmented Reality Marker of Open Computer Vision Package." Sustainability 15, no. 11 (2023): 8887. http://dx.doi.org/10.3390/su15118887.

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An easy method to evaluate a remote place’s snowpack depth has been discussed for helping later-stage elderly persons’ life. The method of using a smartphone camera and an augmented reality marker (AR marker) has been investigated. The general smartphone with a high image resolution camera was used to observe snowpack depth in remote places and remote control the robot via Bluetooth device. And image processing using artificially integrated technology (AI technology) was adapted for detecting the AR markers and for evaluating the snowpack depth.
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Kühnemund, Alexander, Sven Götz, and Guido Recke. "Automatic Detection of Group Recumbency in Pigs via AI-Supported Camera Systems." Animals 13, no. 13 (2023): 2205. http://dx.doi.org/10.3390/ani13132205.

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The resting behavior of rearing pigs provides information about their perception of the current temperature. A pen that is too cold or too warm can impact the well-being of the animals as well as their physical development. Previous studies that have automatically recorded animal behavior often utilized body posture. However, this method is error-prone because hidden animals (so-called false positives) strongly influence the results. In the present study, a method was developed for the automated identification of time periods in which all pigs are lying down using video recordings (an AI-suppo
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Song, Geun-Ho, Ju-Young Lee, Jong-Seop Yang, and Hoe-Kyung Jung. "EDGE AI Based Inference of Multiple Camera Streams using Multiplexing Method for POSE Estimation." JOURNAL OF THE KOREA CONTENTS ASSOCIATION 23, no. 12 (2023): 68–75. http://dx.doi.org/10.5392/jkca.2023.23.12.068.

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Tak, Sehyun, Jong-Deok Lee, Jeongheon Song, and Sunghoon Kim. "Development of AI-Based Vehicle Detection and Tracking System for C-ITS Application." Journal of Advanced Transportation 2021 (August 18, 2021): 1–15. http://dx.doi.org/10.1155/2021/4438861.

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There are various means of monitoring traffic situations on roads. Due to the rise of artificial intelligence (AI) based image processing technology, there is a growing interest in developing traffic monitoring systems using camera vision data. This study provides a method for deriving traffic information using a camera installed at an intersection to improve the monitoring system for roads. The method uses a deep-learning-based approach (YOLOv4) for image processing for vehicle detection and vehicle type classification. Lane-by-lane vehicle trajectories are estimated by matching the detected
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Yang, Liangliang, Tomoki Noguchi, and Yohei Hoshino. "Development of a Grape Cut Point Detection System Using Multi-Cameras for a Grape-Harvesting Robot." Sensors 24, no. 24 (2024): 8035. https://doi.org/10.3390/s24248035.

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Harvesting grapes requires a large amount of manual labor. To reduce the labor force for the harvesting job, in this study, we developed a robot harvester for the vine grapes. In this paper, we proposed an algorithm that using multi-cameras, as well as artificial intelligence (AI) object detection methods, to detect the thin stem and decide the cut point. The camera system was constructed by two cameras that include multi-lenses. One camera is mounted at the base of the robot and named the “base camera”; the other camera is mounted at the robot hand and named the “hand camera” to recognize gra
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Dissertations / Theses on the topic "Camera-AI method"

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Berthet, Alexandre. "Deep learning methods and advancements in digital image forensics." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS252.

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Le volume de données visuelles numériques augmente considérablement d'année en années. En parallèle, l’édition d'images est devenue plus facile et plus précise. Les modifications malveillantes sont donc plus accessibles. La criminalistique des images fournit des solutions pour garantir l’authenticité des données visuelles numériques. Tout d’abord, les solutions étaient des méthodes classiques basées sur les artéfacts produits lors de la création d’une image numérique. Puis, comme pour d’autres domaines du traitement d’images, les méthodes sont passées à l’apprentissage profond. Dans un premier
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Book chapters on the topic "Camera-AI method"

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Okada, Satoshi, and Takuho Mitsunaga. "An Improved Technique for Generating Effective Noises of Adversarial Camera Stickers." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-4581-4_21.

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AbstractCyber-physical systems (CPS) represent the integration of the physical world with digital technologies and are expected to change our everyday lives significantly. With the rapid development of CPS, the importance of artificial intelligence (AI) has been increasingly recognized. Concurrently, adversarial attacks that cause incorrect predictions in AI models have emerged as a new risk. They are no longer limited to digital data and now extend to the physical environment. Thus, they are pointed out to pose serious practical threats to CPS. In this paper, we focus on the “adversarial came
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Staudenrausch, Tim, and Bernd Lüdemann-Ravit. "Cycle Time Measurement Using AI-Based Object Detection and Tracking in Industrial Processes." In ARENA2036. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88831-1_22.

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Abstract This paper presents an AI-based system for improving cycle time measurement in industrial environments, leveraging YOLOv8 for object detection and ByteTrack for tracking. Our non-invasive approach analyzes video from an Azure Kinect camera to calculate cycle times by detecting objects and monitoring their state changes. Tested at the University of Applied Sciences Kempten’s demo plant, the system showcased high accuracy against ground truth data, highlighting its potential to enhance production line monitoring and efficiency significantly. This work contributes to industrial automatio
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Solheiro, Hermenegildo, Lee Kent, and Keisuke Toyoda. "3-2-3 Multi-AI Segmentation Framework: LoD-Based, Incremental Segmentation of 3D Scan Data Using Any 2D AI." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-78593-1_8.

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AbstractIn the age of spatial computing, computer vision is central, and efficient segmentation of 3D scan data becomes a fundamental task. Existing segmentation methods are often locked to specific AI models, lack level-of-detail (LoD) capabilities, and do not support efficient incremental segmentation. These limitations hinder their application to XR systems that integrate architectural and urban scales, which demand both at scale and detailed, up-to-date segmentation information, while leveraging limited local hardware in distributed computing environments.In this work, we present a novel f
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Chung, Chih-Chung, Bo-Chi Chen, Te-Wei Tseng, and Yun-Tzu Lee. "The Slope Monitoring Using Embedded System with Optical-Thermal Image Fusion and Machine Learning." In Progress in Landslide Research and Technology, Volume 3 Issue 1, 2024. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-55120-8_12.

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AbstractTaiwan is at the junction of tectonic plates, with high mountainous terrain and abundant rainfall due to the rich moisture of the subtropical monsoon zone, which makes the already dangerous slopes even more unstable. By applying the digital camera measurement approach, with its moderate installation cost, high security, and mobility, it is possible to capture and monitor the hillside over an extended period, guaranteeing its stability. Photogrammetry is a recent technology that has gained popularity in many fields. Image analysis, achieved by capturing photographs, is a growing trend.
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Ummeaiman, Nishat Subaita, Saba Fatima, Mr Mahantesh P, Benazir M, and Aarif Makandar. "REAL TIME DETECTION AND ANALYSIS OF INDIAN SIGN LANGUAGE USING AI & ML." In Futuristic Trends in Computing Technologies and Data Sciences Volume 3 Book 3. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bfct3p6ch2.

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The primary goal of real-time Indian sign language analysis and detection using AI&ML is to develop a useful method of hand motion conversation between normal and speech impaired people. The technique can be used in conjunction with a webcam or other built-in camera that detects and analyses signals for recognition. Additionally, when new gestures are introduced, the models must be more precise for which databases must be expanded up. In this study, a review of earlier models is conducted, and disadvantages such as environmental variables that influence detection accuracy, such as low ligh
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Hoang, Minh Long. "Deep Learning in Object Detection for the Autonomous Car." In Artificial Intelligence Development in Sensors and Computer Vision for Health Care and Automation Application. BENTHAM SCIENCE PUBLISHERS, 2024. https://doi.org/10.2174/9789815313055124010007.

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This chapter explores the practical application of artificial intelligence (AI) techniques in self-driving cars, mainly focusing on object recognition. Deep learning has emerged as a powerful tool for object detection, playing a crucial role in processing data from lidar, radar, and video cameras. These three technologies are essential components of autonomous vehicles, providing critical obstacle information that enables the automatic system to execute appropriate actions based on the received data. We delve into three advanced techniques that enhance object detection capabilities in autonomo
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Hemalakshmi, K., and A. Muthukumaravel. "Efficient Feature Extraction Method for Traffic Surveillance in Intelligent Transportation Systems." In Cross-Industry AI Applications. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5951-8.ch008.

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As the use of automobiles increases, traffic control surveillance becomes a significant problem in the real world. For effective urban traffic management, real-time, accurate, and reliable traffic flow information must be gathered. This chapter's primary goal is to create an adaptive model that can evaluate real-time vehicle tracking on urban roadways using computer vision techniques. This study proposes the implementation of the improved particle swarm optimization (IPSO) algorithm to extract features that can be used for detailed object analysis. The traffic flow data is pre-processed for en
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Meigal, Alexander Yu, Dmitry G. Korzun, Alex P. Moschevikin, Sergey Reginya, and Liudmila I. Gerasimova-Meigal. "Ambient Assisted Living At-Home Laboratory for Motor Status Diagnostics in Parkinson's Disease Patients and Aged People." In Tools and Technologies for the Development of Cyber-Physical Systems. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-7998-1974-5.ch007.

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The chapter summarizes the authors' development on the concept of “at-home lab” (AHL). The concept employs the methods of artificial intelligence (AI), smart internet of things (IoT) technologies, and data mining techniques. The aim is at support for patients with Parkinson's disease and aged people to continuously monitor and evaluate their motor and cognitive status using own smartphone (in particular, IMU as wearable sensor, apps for testing cognitive status, camera for motor tracking). In addition, other devices in the IoT environment can participate in creating the information assistance
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Meigal, Alexander Yu, Dmitry G. Korzun, Alex P. Moschevikin, Sergey Reginya, and Liudmila I. Gerasimova-Meigal. "Ambient Assisted Living At-Home Laboratory for Motor Status Diagnostics in Parkinson's Disease Patients and Aged People." In Research Anthology on Supporting Healthy Aging in a Digital Society. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5295-0.ch047.

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The chapter summarizes the authors' development on the concept of “at-home lab” (AHL). The concept employs the methods of artificial intelligence (AI), smart internet of things (IoT) technologies, and data mining techniques. The aim is at support for patients with Parkinson's disease and aged people to continuously monitor and evaluate their motor and cognitive status using own smartphone (in particular, IMU as wearable sensor, apps for testing cognitive status, camera for motor tracking). In addition, other devices in the IoT environment can participate in creating the information assistance
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Bondhopadhyay, Banashree, Navya Aggarwal, and Shinjini Sen. "Deep Learning for Tumor Classification." In Cancer Diagnosis, Treatment and Care. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-5400-1.ch010.

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This chapter addresses the urgent need for advanced diagnostic methods in breast cancer, which has become the most prevalent cancer among women globally. Radiological techniques such as Positron Emission Tomography - Computed Tomography (PET-CT) and Gamma Camera offer non-invasive, high-resolution imaging crucial for accurate diagnosis and staging. The increasing incidence of breast cancer underscores the demand for faster and more precise diagnostic tools, which Artificial Intelligence (AI) and Machine Learning (ML) can fulfil. This review explores the application of deep learning and neural
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Conference papers on the topic "Camera-AI method"

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Thoma, Jiri, Josef Cupal, Aimira Baitieva, Jakub Cerny, and Jan Grundel. "Single-shot AI-based point spread function method for an active camera alignment." In Optical Instrument Science, Technology, and Applications III, edited by Richard N. Youngworth, Breann N. Sitarski, and Holger Münz. SPIE, 2024. http://dx.doi.org/10.1117/12.3029509.

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Khan, Hikmat, Charles Johnson, Nidhal Bouaynaya, Ghulam Rasool, Lacey Thompson, and Tyler Travis. "Deep Ensemble for Rotorcraft Attitude Prediction." In Vertical Flight Society 77th Annual Forum & Technology Display. The Vertical Flight Society, 2021. http://dx.doi.org/10.4050/f-0077-2021-16854.

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Historically, the rotorcraft community has experienced a higher fatal accident rate than other aviation segments, including commercial and general aviation. To date, traditional methods applied to reduce incident rates have not proven hugely successful for the rotorcraft community. Recent advancements in artificial intelligence (AI) and the application of these technologies in different areas of our lives are both intriguing and encouraging. When developed appropriately for the aviation domain, AI techniques may provide an opportunity to help design systems that can address rotorcraft safety c
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Santos, Ricardo C. Câmara de M., Mateus Coelho Silva, Rodrigo Lucas Santos, Emerson Klippel, and Ricardo A. R. Oliveira. "A Mobile Robot Based on Edge AI." In Seminário Integrado de Software e Hardware. Sociedade Brasileira de Computação - SBC, 2023. http://dx.doi.org/10.5753/semish.2023.230539.

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Recent advancements in technology have enabled the emergence of Industry 4.0, this term is used to describe the integration of various advanced technologies such as artificial intelligence and robotics in industrial settings. The presence of defective products during production incurs additional costs, and traditional manual methods of equipment inspection prove to be inefficient in such a dynamic environment. In this study, we introduce a robot designed specifically for this scenario, capable of performing tasks that require autonomous movement to specific areas of an industrial plant. To ach
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Mehrishal, S., J. Kim, and J. J. Song. "AI-Powered Semi-Automated Trace Detection Techniques on 3D Digital Rock Mass Models." In 58th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2024. http://dx.doi.org/10.56952/arma-2024-0911.

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ABSTRACT: Estimating rock mass structure relies heavily on deciphering trace lines on exposed rock surfaces. Manual detection of traces on 3D digital models can be tedious and time-consuming. This study proposes a novel AI-driven approach to enhance 3D trace surveying, overcoming potential limitations. A custom pixel-wise texture mapper algorithm transforms 3D rock models into virtual 2D images, eliminating access restrictions. DeepLabV3+, a deep-learning network, efficiently detects trace lines within these virtual images. The detected traces are transformed into 3D data through a multi-step
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Gendron, Blake, Qazi Saeed, and Syed Haider. "Leveraging Artificial Intelligence & Fixed, Continuous Methane Monitoring to Identify Fugitive Emissions Rapidly." In SPE Conference at Oman Petroleum & Energy Show. SPE, 2025. https://doi.org/10.2118/224846-ms.

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Abstract Flared and fugitive methane leaks comprise the bulk of overall greenhouse gas emissions (GHG) from the upstream energy sector and unlike routine flaring is not easily predictable and avoidable (nor is it visible to the naked eye like open-air flaring). There are a number of technologies used to identify and quantify fugitive methane emissions, among which are incumbent technologies such as satellites and optical gas imaging (OGI) camera surveys, each with benefits & drawbacks related to cost, continuity of measurement, probability of detection, and accuracy of quantification, amon
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Oprea, Marin. "INTEGRATION OF ARTIFICIAL INTELLIGENCE IN STEM EDUCATION THROUGH IOT PROJECTS BASED ON MACHINE LEARNING." In eLSE 2021. ADL Romania, 2021. http://dx.doi.org/10.12753/2066-026x-21-096.

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Artificial Intelligence (AI) is widely present in our daily lives: smartphones facial recognition systems, digital voice assistants, smart home devices, mobile banking, Google predictive searches, Netflix recommendation, Google Maps, ride-sharing apps, mobile banking etc. The field of AI is in a continuous and rapid development. This aspect gives to AI the status of a central pole in the process of digital transformation of society. The impact of AI on the Education sector is particularly visible: differentiated and individualized learning, automatic admin tasks, tutoring and support outside t
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Poudanien, Yurii, and Andriy Kozhemiako. "TRENDS IN THE USE OF ARTIFICIAL INTELLIGENCE IN ENDOSCOPY." In 17th IC Measurement and Control in Complex Systems. VNTU, 2024. https://doi.org/10.31649/mccs2024.5-13.

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This study provides a comprehensive overview of current trends in the application of artificial intelligence (AI) in endoscopic examinations of the gastrointestinal tract (GIT). AI significantly enhances medical diagnostic capabilities, particularly in detecting early signs of oncological and other diseases of the GIT. The analysis highlights the advantages and disadvantages of AI as an auxiliary tool for gastroenterologists, capable of improving examination 4 accuracy and reducing the risk of missing pathologies that are difficult to recognize during the procedure. Particular attention is giv
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Valvano, G., A. Rossi, G. Caridi, et al. "Automatic Electrical Wiring Inspection with Advanced Computer Vision Models." In ADIPEC. SPE, 2024. http://dx.doi.org/10.2118/222543-ms.

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Abstract Safety and reliability are paramount in energy industries. In this context, guaranteeing precise electrical wiring connections within terminal blocks is crucial for maintaining quality standards and enabling efficient remote support for on-site installations. Unfortunately, the current wiring quality checks are time-consuming and repetitive, and they are prone to human errors. This situation has led to an increasing interest in leveraging the capabilities of Artificial Intelligence (AI) to expedite the inspection process. AI assistants can either help in or completely automate the ted
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Sakirin, Jakkawan, Thaniyaporn Rapeethasanaphong, and Parichat Maleewong. "Aquatic Animal Monitoring System." In IADC/SPE Asia Pacific Drilling Technology Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/209933-ms.

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Abstract Aquatic Animal Monitoring Systemis initiated as part of PTTEP's Ocean for Life strategy as we thrive in enhancing Ocean Health & Biodiversity Monitoring to ensure that PTTEP's offshore operations are friendly and safe to the surrounding environment and aquatic animals. The basis of the Aquatic Animal Monitoring Systemproject focuses on conservation survey and tracking of rare aquatic animals as well as marinebiodiversity. As part of the process, an underwater camera was installed on a jacket leg of PTTEP's platform to allow the video recording of underwater lives. The video footag
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Soares, Gonçalo, and João Madeiras Pereira. "Lift: An Educational Interactive Stochastic Ray Tracing Framework with AI-Accelerated Denoiser." In WSCG'2021 - 29. International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision'2021. Západočeská univerzita, 2021. http://dx.doi.org/10.24132/csrn.2021.3002.36.

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Real-time physically based rendering has long been looked at as the holy grail in Computer Graphics. With theintroduction of Nvidia RTX-enabled GPUs family, light transport simulations under real-time constraint startedto look like a reality. This paper presents Lift, an educational framework written in C++ that explores the RTXhardware pipeline by using the low-level Vulkan API and its Ray Tracing extension, recently made available byKhronos Group. Furthermore, to accomplish low variance rendered images, we integrated the AI-based denoiseravailable from the Nvidia ́s OptiX framework. Lift’s d
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Reports on the topic "Camera-AI method"

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Chien, Stanley, Lauren Christopher, Yaobin Chen, Mei Qiu, and Wei Lin. Origin-Destination Vehicle Counts in Weaving Area Utilizing Existing Field Data. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317719.

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Vehicle weaving describes the vehicle lane changes in areas between consecutive merge and diverge ramp junctions. During heavy traffic, vehicle weaving will slow down traffic, cause congestion, and increase the possibility of crashes. It is desirable to automatically capture the weaving information using camera videos in the weaving areas. The currently existing weaving area analysis is very tedious and labor-intensive. This report describes a novel system that uses the videos simultaneously captured at the entry and exit of the weaving area to find the number and percentage of vehicles from e
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Kampmeier, Mareike, and Jens Greinert. AL590 Cruise Report - Monitoring ecological consequences of marine munition in the Baltic Sea 2023; 17th – 31st March 2023, Kiel (Germany) – Kiel (Germany), „MecoMM-BS - I“. Alkor-Berichte AL590. GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany, 2023. http://dx.doi.org/10.3289/cr_al590.

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ALKOR cruise AL590 took place as part of the project CONMAR (https://conmarmunition.eu/) which is part of the DAM mission sustainMare (https://www.sustainmare.de/). It was the continuation of the munition monitoring started within the BMBF‐funded project UDEMM (Environmental Monitoring for the Delaboration of Munition in the Sea; https://udemm.geomar.de/), the EMFF (European Maritime and Fisheries Fund) ‐funded projects BASTA (Boost Applied munition detection through Smart data detection in and AI workflows; https://www.basta‐munition.eu) and ExPloTect (Ex‐situ, near‐real‐time detection compou
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Keller, Mareike, Aaron J. Becker, Nikolaj Diller, et al. Monitoring ecological consequences of marine munition in the Baltic Sea 2024 - Cruise No. AL622, 14th – 21st October 2024, Kiel (Germany) – Kiel (Germany), „POST-Clear“. GEOMAR Helmholtz Centre for Ocean Research Kiel, Germany, 2024. https://doi.org/10.3289/cr_al622.

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ALKOR cruise AL622 took place as part of the project CONMAR (https://conmarmunition.eu/) which is part of the DAM mission sustainMare (https://www.sustainmare.de/). It was the continuation of the munition monitoring started within the BMBF‐funded project UDEMM (Environmental Monitoring for the Delaboration of Munition in the Sea; https://udemm.geomar.de/), the EMFF (European Maritime and Fisheries Fund) ‐funded projects BASTA (Boost Applied munition detection through Smart data detection in and AI workflows; https://www.basta‐munition.eu) and ExPloTect (Ex‐situ, near‐real‐time detection compou
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