Research on Surface Defects Classification for PET Preform by Fusing Multi-Scale Features by Chunmei Duan, Taochuan Zhang, Lei Han, Huilin Tan

“…Through experimental data analysis, the higher testing detection accuracy of this method is 98.8%, with an average testing accuracy of 97.1%.…”
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Cutaneous non-volar melanoma dermoscopy and histopathology correlation: a systematic review protocol by Giuseppe Argenziano, Rita Bouceiro Mendes, Martinha Henrique, Pedro Augusto-Simões

“…This study will evaluate the evidence regarding this association.Methods and analysis Observational studies eligible for our systematic review will enrol adults with histological cutaneous non-volar melanoma diagnosis and with dermoscopy image analysis. …”
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Deep learning for automated encrustation detection in sewer inspection by Wasiu Yusuf, Hafiz Alaka, Mubashir Ahmad, Wusu Godoyon, Saheed Ajayi, Luqman Olalekan Toriola-Coker, Abdullahi Ahmed

“…By converting the videos into sequential image frames, we subjected them to thorough analysis and several image pre-processing techniques. …”
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Deep Learning-Based Segmentation and Localization in CT Angiography for Coronary Heart Disease Diagnosis by Bo Zhao, Jianjun Peng, Ce Chen, Yongyan Fan, Kai Zhang, Yang Zhang

“…During data pre-processing, several enhancement techniques are employed to augment image quality. …”
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Semi-Supervised Nuclei Instance Segmentation with Category-Adaptive Sampling and Region-Adaptive Attention by Xunci Li, Die Luo, Zimei Wei, Junan Long, Zhiwei Ye

“…Cell nuclei instance segmentation plays a critical role in pathological image analysis. In recent years, fully supervised methods for cell nuclei instance segmentation have achieved significant results. …”
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Early Diagnosis of Knee Osteoarthritis With a Natural Language Processing–Driven Approach Based on Clinician Notes: Development and Validation Study by Narathip Thanyakunsajja, Kulsawasd Jitkajornwanich, Shan Xu, Donghee Shin, Pattama Charoenporn

“…Previous studies mostly focused on using approaches, such as those involving artificial intelligence, to automatically detect knee OA through such data. However, these studies did not incorporate clinicians’ or doctors’ notes (text data) into the analysis, although these data involving reported symptoms and behaviors are already available and easier to collect and access than laboratory data and image data. …”
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P- and S-Wave Velocity Structures and the Influence of Volcanic Activities in the East Java Area From Seismic Tomography by Syawaldin Ridha, Sukir Maryanto, Agustya A. Martha, Vanisa Syahra, Muhajir Anshori, Pepen Supendi, Sri Widiyantoro, Sri D. Wuryani, Rendi P. Hab Sari

“…This research is mainly aimed at identifying the influence of the volcanic activities by tomography analysis. The data of the earthquakes was recorded by 22 seismic stations of the Indonesia Tsunami Early Warning System (InaTEWS) seismic network in the period of 2009–2017. …”
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VAD-CLVA: Integrating CLIP with LLaVA for Voice Activity Detection by Andrea Appiani, Cigdem Beyan

“…Subsequently, embeddings from these encoders are fused through a deep neural network to perform VAD. Our experimental analysis across three VAD benchmarks showcases the superior performance of our method compared to existing visual VAD approaches. …”
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The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis by Zeyu Chen, Zheng Lin, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

“…Artificial intelligence (AI) algorithms, including principal component analysis, support vector machine, random survival forest, and convolutional neural network, could be applied to the procedure of IPF prognostic model, that is, region of interest extraction, image feature selection, clinical feature selection, and model construction. …”
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The Process of Creating a Digital Communication Model for the Vatican by Józef Kloch

“… In 1978, in the Holy See, all communication took place thanks to the analogue techno­logy of text, sound and image recording. In the following years, the progress in computer science, made it possible to save any kind of data in the form of digital recording, so that one could collect data and transfer it to any place in an instant. …”
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A PET-CT radiomics model for immunotherapy response and prognosis prediction in patients with metastatic colorectal cancer by Wenbiao Chen, Peng Zhu, Yeda Chen, Guoping Sun

“…High-dimensional radiomic features were extracted from PET/CT images using a deep neural network (DNN), and RNA-Seq was used to screen for features associated with TME phenotypes to construct a radiomic score (Rad-Score). …”
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A Garbage Detection and Classification Method Based on Visual Scene Understanding in the Home Environment by Yuezhong Wu, Xuehao Shen, Qiang Liu, Falong Xiao, Changyun Li

“…Aiming at the problems of complex systems with data source and cloud service center data transmission delay and untimely response, at the same time, in order to realize the perception, storage, and analysis of massive multisource heterogeneous data, a garbage detection and classification method based on visual scene understanding is proposed. …”
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Building digital histology models of transcriptional tumor programs with generative deep learning for pathology-based precision medicine by Hanna M. Hieromnimon, James Dolezal, Kristina Doytcheva, Frederick M. Howard, Sara Kochanny, Zhenyu Zhang, Robert L. Grossman, Kevin Tanager, Cindy Wang, Jakob Nikolas Kather, Evgeny Izumchenko, Nicole A. Cipriani, Elana J. Fertig, Alexander T. Pearson, Samantha J. Riesenfeld

“…Methods Our approach detects expression of transcriptional programs from tumor histology and interprets the image features supporting program detection. Specifically, we used RNA-seq data from squamous cell carcinoma (SCC) patients to infer cohesive expression patterns of multiple genes. …”
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Evaluation of Morphometric Factors on the Distribution of Debris: A Case Study on the Attica Ripples on the South of Paveh- Kermanshah Province, Iran by Mohammad Ahmadi

“…An area of ​​120 square kilometers was identified on the classified image. The network was designed in two dimensions in two kilometers. …”
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Improving 3D deep learning segmentation with biophysically motivated cell synthesis by Roman Bruch, Mario Vitacolonna, Elina Nürnberg, Simeon Sauer, Rüdiger Rudolf, Markus Reischl

“…Furthermore, we present a generative adversarial network (GAN) training scheme that generates not only image data but also matching labels. …”
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Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study. by Eugene Duff, Fernando Zelaya, Fidel Alfaro Almagro, Karla L Miller, Naomi Martin, Thomas E Nichols, Bernd Taschler, Ludovica Griffanti, Christoph Arthofer, Gwenaëlle Douaud, Chaoyue Wang, Thomas W Okell, Richard A I Bethlehem, Klaus Eickel, Matthias Günther, David K Menon, Guy Williams, Bethany Facer, David J Lythgoe, Flavio Dell'Acqua, Greta K Wood, Steven C R Williams, Gavin Houston, Simon S Keller, Catherine Holden, Monika Hartmann, Lily George, Gerome Breen, Benedict D Michael, Peter Jezzard, Stephen M Smith, Edward T Bullmore, COVID-CNS Consortium

“…We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data.…”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…AI-powered video analysis devices for mining applications were designed to enable image-based hazard identification. …”
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Crack Development in Compacted Loess Subjected to Wet–Dry Cycles: Experimental Observations and Numerical Modeling by Yu Xi, Mingming Sun, Gang Li, Jinli Zhang

“…This article examines the influence of initial moisture content, dry density, and thickness on crack formation in compacted loess subjected to wet–dry cycles, using both laboratory experiments and numerical simulation analysis. It quantitatively analyzes the process of crack evolution using digital image processing technology. …”
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Realistic Speech-Driven Talking Video Generation with Personalized Pose by Xu Zhang, Liguo Weng

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Learnable Resized and Laplacian-Filtered U-Net: Better Road Marking Extraction and Classification on Sparse-Point-Cloud-Derived Imagery by Miguel Luis Rivera Lagahit, Xin Liu, Haoyi Xiu, Taehoon Kim, Kyoung-Sook Kim, Masashi Matsuoka

“…Addressing this, we propose improving U-Net’s ability to extract and classify road markings from sparse-point-cloud-derived images by introducing a learnable resizer (LR) at the input stage and learnable resizer blocks (LRBs) throughout the network, thereby mitigating feature and localization degradation from resizing operations in the deep learning framework. …”
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