Adulate 发表于 2025-3-23 13:45:29
,Robust Unsupervised Geo-Spatial Change Detection Algorithm for SAR Images, unsupervised grid graph generation algorithm specifically designed for change detection using Synthetic Aperture Radar (SAR) images. The proposed technique encompasses a multi-step process: starting with an improved log-ratio based difference image generation, followed by shortest path vector compuintellect 发表于 2025-3-23 16:33:42
http://reply.papertrans.cn/25/2423/242299/242299_12.png虚构的东西 发表于 2025-3-23 21:12:15
http://reply.papertrans.cn/25/2423/242299/242299_13.pnggraphy 发表于 2025-3-24 01:23:16
http://reply.papertrans.cn/25/2423/242299/242299_14.pngCreatinine-Test 发表于 2025-3-24 04:02:29
http://reply.papertrans.cn/25/2423/242299/242299_15.png减去 发表于 2025-3-24 08:37:14
http://reply.papertrans.cn/25/2423/242299/242299_16.png云状 发表于 2025-3-24 11:17:40
MuSTAT: Face Ageing Using Multi-scale Target Age Style Transfer,age gap. Although this can be solved using data collected over long age spans, it is challenging and tedious. This work proposes a multi-scale target age-based style face ageing model using an encoder-decoder architecture to generate high-fidelity face images under ageing. Further, we propose usingEncephalitis 发表于 2025-3-24 15:09:41
,Efficient Contextual Feature Network for Single Image Super Resolution,g feature utilization through complex layer connections. However, these methods may not be suitable for resource-constrained devices due to their computational demands. We propose a novel approach called Efficient Contextual Feature Network (ECFN) to address this issue. ECFN utilizes two convolutionOpponent 发表于 2025-3-24 20:22:22
T-Fusion Net: A Novel Deep Neural Network Augmented with Multiple Localizations Based Spatial Attenworks. Nonetheless, the growing complexity of datasets and the ongoing pursuit of enhanced performance necessitate innovative approaches. In this study, we introduce a novel deep neural network, referred to as the “T-Fusion Net,” which incorporates multiple spatial attention mechanisms based on locaGEST 发表于 2025-3-24 23:51:25
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