Titlebook: Artificial Neural Networks and Machine Learning – ICANN 2023; 32nd International C Lazaros Iliadis,Antonios Papaleonidas,Chrisina Jay Confe

mettlesome

,An Auxiliary Modality Based Text-Image Matching Methodology for?Fake News Detection,ists of four components: one fusion module and three matching modules, where the former one joints text and image features, and the latter three computes the corresponding similarities among textual, visual, and auxiliary modalities. Aligning them with different weights, and connecting them with a c

HAUNT

An Improved YOLOv5 with Structural Reparameterization for Surface Defect Detection,rk to focus on detecting small targets. The experimental results on the Northeastern University (NEU) surface defect database show that, our model is superior to the state-of-the-art detectors, such as the original YOLOv5, Fast-RCNN in accuracy and speed.

雜役

ASP Loss: Adaptive Sample-Level Prioritizing Loss for Mass Segmentation on Whole Mammography Imagesvery sample, to prioritize the contribution of each loss term accordingly. As one of the variations of U-Net, AU-Net is selected as the baseline approach for the evaluation of the proposed loss. The ASP loss could be integrated with other existing mass segmentation approaches to enhance their perfor

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libertine

吹牛者

,Combining Edge-Guided Attention and?Sparse-Connected U-Net for?Detection of?Image Splicing,omplementary relationship between splicing regions and their boundaries. Thirdly, in order to achieve more precise positioning results, SCU is used as postprocessing for removing false alarm pixels outside the focusing regions. In addition, we propose an adaptive loss weight adjustment algorithm to

劇本

,Contour-Augmented Concept Prediction Network for?Image Captioning,tion. Extensive experimental results on MS COCO dataset demonstrate the effectiveness of our method and each proposed module, which can obtain 40.6 BLEU-4 and 135.6 CIDEr scores. Code will be released in the final version of the paper.

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