PoWBWM: Proof of work consensus cryptographic blockchain-based adaptive watermarking system for tamper detection applications by P. Aberna, L. Agilandeeswari

“…The advances in photography technology have made it possible to capture real-time high-dynamic-range (HDR) images through an iPhone or an Android device, which highlights the need for rigorous research on HDR images for tamper detection, and localization. …”
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Hamstring Activity Before and After Break-Point Angle Calculated By Smartphone Application During the Nordic Hamstring Exercise by Toshiaki Soga, Shota Yamaguchi, Takayuki Inami, Hiromi Saito, Nadaka Hakariya, Naoto Nakaichi, Sho Shinohara, Koki Sasabe, Hayato Nakamura, Teerapat Laddawong, Kei Akiyama, Norikazu Hirose

“…BPA during NHE was calculated using the Nordic Angle app by analyzing a movie recorded with an iPhone camera. Additionally, the knee flexion angle during NHE was determined using two-dimensional motion analysis software based on video data. …”
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Neural correlates of the non-optimal price: an MEG/EEG study by Aleksei Gorin, Elizaveta Kuznetsova, Andrew Kislov, Egor Levchenko, Vasily Klucharev, Victoria Moiseeva, Anna Yurchenko, Alexander Luzhin, Natalia Galkina, Anna N. Shestakova

“…In each trial, participants were exposed to a mobile phone image (iPhone, Nokia, or Xiaomi) followed by a price, and instructed to judge whether the price was high or low based on a target word (“cheap” or “expensive”).ResultsIn both EEG experiments, we found a strong N400-like response to the incongruent target words following prices that substantially differed from the real market value of the mobile phone. …”
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Ideal Illumination for Smartphone-based Trabeculectomy Bleb Photography by Gagan Kalra, Parul Ichhpujani, Sahil Thakur, Urvashi Sharma

“…Native camera application and FiLMiC pro camera application were used on iPhone X to compare bleb images using yellow and white pen-torches as illumination source. …”
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Estimating Maxillary Sinus Volume Using Smartphone Camera by Christoforos Meliadis, Emily Feng, Ezekiel Johnson, Wendy Zhu, Paramesh Gopi, Vivek Mohan, Peter H. Hwang, Jacob Johnson, Bryant Y. Lin

“…<italic>Methods:</italic> We recruited 40 participants to conduct a comparative analysis between Computed Tomography (CT) and face scans obtained using an Apple iPhone. Utilizing Apple&#x0027;s ARKit for 3D facial mesh modeling, we estimated sinus dimensions based on established craniofacial landmarks and calculated the volume through a geometric approximation of the maxillary sinus. …”
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BDMANGO: An image dataset for identifying the variety of mango based on the mango leavesMendeley Data by Mohammad Manzurul Islam, Md. Jubayer Ahmed, Mahmud Bin Shafi, Aritra Das, Md. Rakibul Hasan, Abdullah Al Rafi, Mohammad Rifat Ahmmad Rashid, Nishat Tasnim Niloy, Md. Sawkat Ali, Abdullahi Chowdhury, Ahmed Abdal Shafi Rasel

“…The images were captured using the rear cameras of a Google Pixel 6a and an iPhone XR and were stored in 640 × 480 pixels resolution. …”
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Low-cost phone-based LiDAR scanning technology provides sub-centimeter accuracy when measuring the main dimensions of motor-manual tree felling cuts by Stelian Alexandru Borz, Andrea Rosario Proto

“…Close-range (up to 50 cm) scans were taken on each notch by an iPhone 13 Pro Max platform using the freely available software 3D Scanner App. …”
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Framework for smartphone-based grape detection and vineyard management using UAV-trained AI by Sergio Vélez, Mar Ariza-Sentís, Mario Triviño, Antonio Carlos Cob-Parro, Miquel Mila, João Valente

“…Then, YOLO is trained using the videos and further applied to images taken by farmers with common smartphones (Xiaomi Poco X3 Pro and iPhone X). In addition, a web app was developed to connect the system with mobile technology easily. …”
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Getting Real: A Naturalistic Methodology for Using Smartphones to Collect Mediated Communications by Chad C. Tossell, Philip Kortum, Clayton W. Shepard, Ahmad Rahmati, Lin Zhong

“…We also provide a description of a naturalistic logging approach that has been applied successfully to collecting mediated communications from iPhones. The methodology was designed to intentionally decrease reactivity and resulted in data that were more accurate than self-reports. …”
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