Iniquitous
发表于 2025-3-28 17:44:18
Cross-Layer Feature Attention Module for Multi-scale Object Detection,ly one or two layers, failing to obtain consistent results for objects with different scales. In this paper, we propose a cross-layer feature attention module (CFAM) which can be plugged in any off-the-shelf architecture, and demonstrate that attentions obtained from multiple layers can further impr
GROVE
发表于 2025-3-28 19:53:39
Interact-Pose Datasets for 2D Human Pose Estimation in Multi-person Interaction Scene,rounds and the multiplayer scene. However, when facing the scene of multi-person interaction, the results of current mainstream algorithms are still unsatisfactory and some common datasets are not suitable for coping with interaction problems. Therefore, we propose a new dataset named Interact-Pose
空中
发表于 2025-3-29 00:40:53
Multimodal Breast Cancer Diagnosis Based on Multi-level Fusion Network,eening of breast cancer. However, the classification of breast cancer with the data from a single modality is still not accurate enough to meet clinical needs. This paper proposes a Multimodal breast cancer diagnosis based on Multi-level fusion network which integrates pathological images, structure
surrogate
发表于 2025-3-29 06:12:45
Die Matrix-Steifigkeitsmethode, time. With a focus on accuracy, we show that ray-pixel models outperform traditional models in terms of image undistortion, stereo rectification and 3D reconstruction. Our calibration pipeline has been released at ..
护身符
发表于 2025-3-29 08:21:24
Das Konzept der Finite-Element-Methode, Dual-ConvD encoding branch, gradient detecting branch, and multi-category segmentation branch. We used 295 patients as training set and 74 as validation set to validate the performance of the algorithm. The proposed method has 1.25% improved to the latest method on averaged Dice Score.
宣传
发表于 2025-3-29 14:27:24
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感激小女
发表于 2025-3-29 17:40:30
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Entropion
发表于 2025-3-29 21:49:01
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hidebound
发表于 2025-3-30 02:52:17
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olfction
发表于 2025-3-30 05:04:51
Das Konzept der Finite-Element-Methode,to accurately segment. Finally, the pseudo-label image and the original image are combined and input to the improved SegFormer network for training. The experiment results show that, the segmentation effect of the proposed method is better than PSPNet, HRNet and other methods.