Análisis de la implementación software de un conformador de señales ultrasónicas para tiempo real by D. Romero-Laorden, J. Villazón-Terrazas, M. Santos Peñas, M.A. García-Izquierdo, O. Martínez-Graullera

“…Then, using GPGPU techniques, two different implementation alternatives are analysed, showing how proper planning of access to data improves the performance of the algorithm. Palabras clave: Imagen Ultrasónica, Procesamiento de Señal, Computación Paralela, GPU, CUDA, Keywords: Ultrasonic imaging GPU Signal Processing Parallel computing CUDA…”
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Assessment of environmental impacts of armed conflict in Mozambique using remotely sensed data by Focas Francisco Bacar, Hilário Biché Faque

“…To evaluate these effects, we used Multi-temporal satellite images (Landsat 5 TM and Landsat 8 OLI-TIRS) in combination with fieldwork, geographic information systems, landscape ecology metrics, and the Random Forest machine learning algorithm. …”
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Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…A key novelty of this work is the integration of a CNN-LSTM-based surrogate model to accelerate the design process by predicting Mach numbers from nozzle images, significantly reducing reliance on computationally expensive CFD simulations. …”
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Automatic 3D reconstruction of indoor building point clouds under occlusion based on gestalt rules by Xiaoli Liang, Yunxiang Liu, Jiayao Wang, Zhiqiang Qin, Lei Chen, Haoxue Jia, Cancong Dai

“…Then, holes in the structural surface are filled using an image inpainting algorithm under a spatial relation constraint. …”
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Unified Dynamic Dictionary and Projection Optimization With Full-Rank Representation for Hyperspectral Anomaly Detection by Hongran Li, Chao Wei, Yizhou Yang, Zhaoman Zhong, Ming Xu, Dongqing Yuan

“…Hyperspectral anomaly detection (HAD) aims to classify each pixel in a hyperspectral image as either background or anomaly without requiring labeled data. …”
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Secure S-box construction with 1D chaotic maps and finite field theory for block cipher encryption by Sajjad Shaukat Jamal, Rashad Ali, Muhammad Kamran Jamil, Sameer Abdullah Nooh, Fahad Alblehai, Gulraiz

“…The article also includes an image encryption approach utilizing S-boxes. Finally, we believe that the strategy for developing long-lasting and reliable s-box solutions for block cipher systems contributes significantly to subsequent studies on architectural principles.…”
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Manifold embeddings achieve comparable performance with multispectral imagery for time-series based land disturbance detection by Mengyao Li, Jianbo Qi, Su Ye, Qiao Wang

“…The resulting manifold embeddings are applied to the Continuous Change Detection and Classification (CCDC) algorithm for land disturbance detection. Two key findings emerge: (1) We developed a general UMAP-based dimensionality reduction model that works across global seasons, with manifold embeddings preserving time series coherence and exhibiting stable value ranges. (2) The embeddings achieved comparable performance to full-spectrum multispectral data in image prediction and disturbance detection with CCDC. …”
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TLDDM: An Enhanced Tea Leaf Pest and Disease Detection Model Based on YOLOv8 by Jun Song, Youcheng Zhang, Shuo Lin, Huijie Han, Xinjian Yu

“…Initially, the C2f-Faster-EMA module is employed to reduce the number of parameters and model complexity while enhancing image feature extraction capabilities. Furthermore, the Deformable Attention mechanism is integrated to improve the model’s adaptability to spatial transformations and irregular data structures. …”
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Clear Cell Acanthoma/Pseudolymphoma: Clinical­ Dermatoscopic and Histological Correlation by Shulaia T., Kiladze N., Miriamidze A.

“…For the immersion dermatoscopy ultrasound gel was used. All obtained images were estimated in accordance with the algorithm of G. …”
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Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks by Haikun Shang, Yanlei Wei, Shen Zhang

“…The approach begins by extracting features from DGA data using the ratio method and Multiscale sample entropy (MSE), then reconstructs the state space of the feature data using recursive plots to generate interpretable two-dimensional image features. A deep feature extraction process is performed using the ResNet50 model, integrated with the Convolutional Block Attention Module (CBAM). …”
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YOLO-HPSD: A high-precision ship target detection model based on YOLOv10. by Manlin Zhu, Dezhi Han, Bing Han, Xiaohu Huang

“…This study proposes a high-precision ship target detection algorithm based on YOLOv10, named YOLO-HPSD (High-precision Ship Target Detection). …”
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Research on downhole drilling target detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…To monitor the drilling process in real time and enhance the efficiency of target detection at underground coal mine drill sites, an improved algorithm based on Yolov8n has been proposed, which offers advantages compared with the traditional detection methods. …”
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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…Firstly, SqueezeNet enables efficient feature extraction from segmented fundus images with minimal computational complexity, ensuring that critical retinal features are captured effectively. …”
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Existing Buildings Recognition and BIM Generation Based on Multi-Plane Segmentation and Deep Learning by Dejiang Wang, Jinzheng Liu, Haili Jiang, Panpan Liu, Quanming Jiang

“…This paper proposes an automated approach to BIM modeling of the external surfaces of existing buildings, aiming to streamline the labor-intensive and time-consuming processes of manual measurement and drafting. Initially, multi-angle images of the building are captured using drones, and the building’s point cloud is reconstructed using 3D reconstruction software. …”
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Hierarchical Embedded System Based on FPGA for Classification of Respiratory Diseases by Trong-Thanh Han, Kien Le Trung, Phuong Nguyen Anh, Anh Do Trung

“…The fourth layer utilizes Wavelet Transform to convert breathing patterns into Spectrogram images, which the Artificial Neural Network processes for disease diagnosis. …”
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Cattle identification based on multiple feature decision layer fusion by Dongxu Li, Baoshan Li, Qi Li, Yueming Wang, Mei Yang, Mingshuo Han

“…The method utilizes the SOLO algorithm to segment images and employs the FaceNet and PP-OCRv4 networks to extract features for the cattle’s faces, muzzle patterns, and ear tags. …”
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Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

“…The failure to generalize did not improve even when the tinctorial difference corrections were made through either traditional color-tuning or stain normalization with the help of a Cycle Generative Adversarial Network (CycleGAN) process. This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
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Using a Camera System for the In-Situ Assessment of Cordon Dieback due to Grapevine Trunk Diseases by Julie Tang, Olivia Yem, Finn Russell, Cameron A. Stewart, Kangying Lin, Hiranya Jayakody, Matthew R. Ayres, Mark R. Sosnowski, Mark Whitty, Paul R. Petrie

“…The assessment of grapevine trunk disease symptoms is a labour-intensive process that requires experience and is prone to bias. …”
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A cotton organ segmentation method with phenotypic measurements from a point cloud using a transformer by Fu-Yong Liu, Hui Geng, Lin-Yuan Shang, Chun-Jing Si, Shi-Quan Shen

“…This study proposes a cotton point cloud organ semantic segmentation method named TPointNetPlus, which combines PointNet++ and Transformer algorithms. Firstly, a dedicated point cloud dataset for cotton plants is constructed using multi-view images. …”
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A New Approach for Deep Gray Matter Analysis Using Partial-Volume Estimation. by Guillaume Bonnier, Tobias Kober, Myriam Schluep, Renaud Du Pasquier, Gunnar Krueger, Reto Meuli, Cristina Granziera, Alexis Roche

“…<h4>Introduction</h4>The existence of partial volume effects in brain MR images makes it challenging to understand physio-pathological alterations underlying signal changes due to pathology across groups of healthy subjects and patients. …”
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