A hybrid parallel convolutional spiking neural network for enhanced skin cancer detection by K. Anup Kumar, C. Vanmathi

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Effects of scale on segmentation of Nissl–stained rat brain tissue images via convolutional neural networks by Alexandro Arnal, Olac Fuentes

“…Currently, it is not clear what scale of the input tissue images offers the most information for these models to exploit. In this work, we test a fully convolutional architecture, U–Net, with Nissl–stained rat brain tissue images of different scales. …”
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Foundations of sustainable construction management with international benchmarking by AbdulLateef Olanrewaju

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The European Green Deal Industrial Plan: Risks and Opportunities. The Chances of the Romanian Economy by Strautsiu E., Melintei M.

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Efficiency Estimation of Constructing of Wind Power Plant for the Heat Supply Needs by A. V. Bezhan

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Design and development of an efficient RLNet prediction model for deepfake video detection by Varad Bhandarkawthekar, T. M. Navamani, Rishabh Sharma, K. Shyamala

“…While existing methods often focus on spatial features, they may overlook crucial temporal information distinguishing real from fake content and need to investigate several other Convolutional Neural Network architectures on video-based deep fake datasets.MethodsThis study introduces an RLNet deep learning framework that utilizes ResNet and Long Short Term Memory (LSTM) networks for high-precision deepfake video detection. …”
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Deep learning-driven 3D marine nitrate estimation: uncertainty mitigation through underwater signal exploitation and label augmentation by Xiang Yu, Guodong Fan, Jinjiang Li

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Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals by Ahmed Shaheen, Liang Ye, Chrishni Karunaratne, Tapio Seppänen

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Fusion of Multimodal Spatio-Temporal Features and 3D Deformable Convolution Based on Sign Language Recognition in Sensor Networks by Qian Zhou, Hui Li, Weizhi Meng, Hua Dai, Tianyu Zhou, Guineng Zheng

“…These modules are combined to capture the spatio-temporal information in multi-stream skeleton features. Secondly, we propose a 3D ResNet model based on deformable convolution (D-ResNet) to model complex spatial and temporal sequences in the original raw images. …”
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Model-Based Deep Network for Single Image Deraining by Pengyue Li, Jiandong Tian, Yandong Tang, Guolin Wang, Chengdong Wu

“…The detection sub-network not only adjusts channel-wise feature responses by our novel channel attention block to pay more attention to learn the rain map, but also combines the context information with the precise localization by the U-DenseNet to promote pixel-wise estimation accuracy. …”
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Digital Analysis Methods in Business-Processes and Projects in Digital Twins at Investment-Construction Companies by A. I. Sukhorukov, E. A. Zakharova, E. V. Shvetsov

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Application Of The Denitrification-Decomposition (DNDC) Model To Retrospective Analysis Of The Carbon Cycle Components In Agrolandscapes Of The Central Forest Zone Of European Russ... by Olga E. Sukhoveeva, Dmitry V. Karelin

“…In  this study the DNDC model was parameterized  for Russian arable soils using official statistical information and data taken from published sources. Three main carbon  variables in agrolandscapes were modelled: soil organic carbon, soil respiration, and net ecosystem exchange over the period of 1990-2017. …”
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A Novel Dual-Branch Global and Local Feature Extraction Network for SAR and Optical Image Registration by Xuanran Zhao, Yan Wu, Xin Hu, Zhikang Li, Ming Li

“…The registration of synthetic aperture radar (SAR) and optical images is significant in obtaining their complementary information, which is a key prerequisite for image fusion. …”
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Efficient and Motion Correction-Free Myocardial Perfusion Segmentation in Small MRI Data Using Deep Transfer Learning From Cine Images: A Promising Framework for Clinical Implement... by German Garcia-Jara, Angel Jimenez-Molina, Esteban Reyes, Nicolas Tapia-Rivas, Cristobal Ramos-Gomez, Jose De Grazia, Matias Sepulveda

“…Through transfer learning, this methodology leverages the wealth of information available from large, publicly accessible cine magnetic resonance datasets, which provide anatomically analogous images to perfusion ones. …”
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Nondestructive detection of sweet potato leaf curl virus using 3D laser imaging combined with deep learning by Yican Yang, Nuwan K. Wijewardane, Tyler J. Slonecki, Phillip A. Wadl, Sharon A. Andreason, Jingdao Chen, Lorin Harvey

“…The findings of our study showed the feasibility of using 3D imaging and employing the deep learning model PointNet++ for non-destructive, rapid detection of SPLCV in sweetpotato.…”
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Modelling radiological features fusion and explainable AI in pneumonia detection: A graph- based deep learning and transformer approach by Pratham Kaushik, Eshika Jain, Vinay Kukreja, Shanmugasundaram Hariharan, Murugaperumal Krishnamoorthy, Vandana Ahuja, Abhishek Bhattacherjee, Rajesh Kumar Kaushal, Shih-Yu Chen

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GAN-enhanced deep learning for improved Alzheimer's disease classification and longitudinal brain change analysis by Purushottam Pandey, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Surbhi Bhatia Khan, Jyoti Pruthi, Eid Albalawi, Ali Algarni, Ahlam Almusharraf

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Discovering High-Level Process Models from Event Logs by Antonina A. Begicheva, Irina A. Lomazov

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Using Event Logs for Local Correction of Process Models by Alexey A. Mitsyuk, Irina A. Lomazova, Wil M.P. van der Aalst

“…In this paper, we consider the problem of process model adjustment (correction) using the information from an event log. The input data for this task are the initial process model (a Petri net) and the event log. …”
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A Novel Parallel Multi-Scale Attention Residual Network for the Fault Diagnosis of a Train Transmission System by Yong Chang, Tengfei Gao, Juanhua Yang, Zongyao Liu, Biao Wang

“…Firstly, multi-scale learning modules (MLMods) with different structures and convolutional kernel sizes are designed by combining a residual neural network (ResNet) and an Inception network, which can automatically learn multi-scale fault information from vibration signals. …”
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