Computational modelling reveals neurobiological contributions to static and dynamic functional connectivity patterns by Linnea Hoheisel, Linnea Hoheisel, Hannah Hacker, Gereon R Fink, Gereon R Fink, Silvia Daun, Silvia Daun, Joseph Kambeitz, Joseph Kambeitz

“…Recent advances in computational modelling allow us to investigate the relationship of both static FC (sFC) and dynamic FC (dFC) with neurobiology non-invasively.In this study, we modelled the brain activity of 200 healthy individuals based on empirical resting-state functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data. …”
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Research on the characteristics of the falling behavior of mixed coal and gangue by SHAN Pengfei, YANG Tong, SUN Haoqiang, XI Bojia

“…Traditional studies on the dynamic characteristics of coal flow during the top coal caving process, based on image detection technology, have primarily focused on specific-stage image analysis, lacking a comprehensive analysis of dynamic characteristics across all stages. …”
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Revolutionizing classification: A novel gray level co-occurrence matrix and statistical feature-based segmentation approach by Abdelwahed Motwakel

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Enhancing prediction of human traits and behaviors through ensemble learning of traditional and novel resting-state fMRI connectivity analyses by Takaaki Yoshimoto, Kai Tokunaga, Junichi Chikazoe

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Computer-Aided Brain Tumor Diagnosis: Performance Evaluation of Deep Learner CNN Using Augmented Brain MRI by Asma Naseer, Tahreem Yasir, Arifah Azhar, Tanzeela Shakeel, Kashif Zafar

“…Analysing Magnetic Resonance Images (MRIs) manually is inadequate for efficient and accurate brain tumor diagnosis. …”
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Design of real-time transmission system for underwater panoramic camera based on RTSP. by Wenhui Wang, Yongqi Li, Rufei He

“…The experimental results show that the data transmission effect and quality of the system are good, and the average reprojection error of the calibrated image is 0.12 pixels; During the process of data collection and transmission, the effective time window of the eye diagram is the largest, and the waveform of the top-level data transmission tends to be stable with the smallest fluctuation amsplitude; Dynamically adjust the data transmission rate, control the network packet loss rate below 0.5%, and improve the real-time transmission efficiency of underwater data.…”
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G-ROBOT: An Intelligent Greenhouse Seedling Height Inspection Robot by Baoqi Wang, Yang Ding, Chunyan Wang, Deyu Li, Hongchang Wang, Zhilong Bie, Yuan Huang, Shengyong Xu

“…The results of the greenhouse experiment showed that the robot has an average battery life of 5.2 h after being fully charged, with satisfactory motion stability and environmental adaptability; the environmental information data collected were valid, and errors were within the acceptable range; the captured seedling crop images were of high quality, and the seedling height data obtained through algorithm analysis were valid and reliable. …”
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Object detection with afordable robustness for UAV aerial imagery: model and providing method by Viacheslav Moskalenko, Artem Korobov, Yuriy Moskalenko

“…Development of a model and method to ensure the robustness of object detectors for aerial image analysis. Methods. Combination of ideas and methods for dynamic neural networks, and methods for robustness and resilience optimization for neural networks. …”
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RETRACTED ARTICLE: A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications by Hadi Hashemzadeh, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Mario Rothbauer, Peter Ertl, Hossein Naderi-Manesh

“…The proposed CAD system completely eliminates the need for extensive user intervention, enabling the processing of large amounts of image data with robust and highly accurate results.…”
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Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution by Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang

“…We used convolutional neural network-based models pretrained on large-scale open-domain data to extract spatial features of CE images that were then used in a dense feed-forward neural network classifier. …”
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ALDP-FL for adaptive local differential privacy in federated learning by Lixin Cui, Xu Wu

“…Regarding the reconstructed images under the iDLG attack, the average improvement rates in MSE and SSIM reach 391.2% and –85.4%, respectively, significantly outperforming all other comparison methods.…”
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Mysterious seismoacoustic signals of eastern Helwan quarry blasts 2022 by Islam Hamama, Shimaa H. Elkhouly, Hanan Gaber, Mona Hamada, Hany S. Elbehiri, Adel S. Othman, Mohamed Maklad, Mona Abdelazim, Mohamed N. ElGabry, Ahmed Lethy, Hesham Hussein, Masa-yuki Yamamoto

“…Infrasound propagation models, coupled with F-K analysis, further confirmed the locations and directions of the recorded events, providing robust data that could be correlated with planet satellite images of the azimuth directions detected via the infrasound array analyses. …”
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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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Research on machine vision online monitoring system for egg production and quality in cage environment by Zhenlong Wu, Hengyuan Zhang, Cheng Fang

“…Experimental results revealed that the henhouse average network latencies of 35 ms, with signal strengths between -30 and -71 dBm, ensuring data transmission to the poultry management system. …”
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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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Exploring the effect of training set size and number of categories on ice crystal classification through a contrastive semi-supervised learning algorithm by Y. Chu, Y. Chu, H. Zhang, X. Li, J. Henneberger

“…The algorithm consists of an upstream unsupervised learning network tasked with extracting meaningful representations from a large number of unlabeled ice crystal images, and a downstream supervised network is fine-tuned with a small subset of labeled images of the entire dataset to perform the classification task. …”
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LGWheatNet: A Lightweight Wheat Spike Detection Model Based on Multi-Scale Information Fusion by Zhaomei Qiu, Fei Wang, Tingting Li, Chongjun Liu, Xin Jin, Shunhao Qing, Yi Shi, Yuntao Wu, Congbin Liu

“…Additionally, when combined with the Slicing Aided Hyper Inference strategy, LGWheatNet further improved the detection accuracy of wheat spikes, especially for small-scale targets and edge regions, when processing large-scale high-resolution images. This strategy significantly enhanced both inference efficiency and accuracy, making it particularly suitable for image analysis from drone-captured data. …”
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A Modified MobileNetv3 Coupled With Inverted Residual and Channel Attention Mechanisms for Detection of Tomato Leaf Diseases by Rubina Rashid, Waqar Aslam, Romana Aziz, Ghadah Aldehim

“…The model is trained using transfer learning with specific adjustments to minimize detection errors and is fine-tuned using a tomato leaf disease image dataset extracted from Plant Village. This feature integration and data analysis scheme are then deployed to provide a tomato leaf disease detection Android app. …”
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Health Monitoring of Carbon Fiber Reinforced Building Materials Based on Phase Unwrapping Algorithm by Min Yan, Jianjun Zhou, Shuai Guo, Yanlong Li

“…When constructing the model, deep convolutional neural network is used to effectively extract the features of carbon fiber reinforced building materials, and improve the analysis ability of the building materials monitoring model. …”
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Digitization of Medical Device Displays Using Deep Learning Models: A Comparative Study by Pedro Ferreira, Pedro Lobo, Filipa Reis, João L. Vilaça, Pedro Morais

“…In addition to these comparisons, we also explore a hybrid approach that combines the YOLOv8l model for object detection with a Convolutional Neural Network (CNN) for classification. Several iterations of the aforementioned models were tested, using image resolutions of 320 × 320 and 640 × 640. …”
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