Iberian Conference on Pattern Recognition and Image Analysis最新文献

Learning to search for and detect objects in foveal images using deep learning 学习使用深度学习在中央凹图像中搜索和检测物体

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2023-04-12 DOI: 10.48550/arXiv.2304.05741

Beatriz Paula, Plinio Moreno

{"title":"Learning to search for and detect objects in foveal images using deep learning","authors":"Beatriz Paula, Plinio Moreno","doi":"10.48550/arXiv.2304.05741","DOIUrl":"https://doi.org/10.48550/arXiv.2304.05741","url":null,"abstract":"The human visual system processes images with varied degrees of resolution, with the fovea, a small portion of the retina, capturing the highest acuity region, which gradually declines toward the field of view's periphery. However, the majority of existing object localization methods rely on images acquired by image sensors with space-invariant resolution, ignoring biological attention mechanisms. As a region of interest pooling, this study employs a fixation prediction model that emulates human objective-guided attention of searching for a given class in an image. The foveated pictures at each fixation point are then classified to determine whether the target is present or absent in the scene. Throughout this two-stage pipeline method, we investigate the varying results obtained by utilizing high-level or panoptic features and provide a ground-truth label function for fixation sequences that is smoother, considering in a better way the spatial structure of the problem. Finally, we present a novel dual task model capable of performing fixation prediction and detection simultaneously, allowing knowledge transfer between the two tasks. We conclude that, due to the complementary nature of both tasks, the training process benefited from the sharing of knowledge, resulting in an improvement in performance when compared to the previous approach's baseline scores.","PeriodicalId":319553,"journal":{"name":"Iberian Conference on Pattern Recognition and Image Analysis","volume":"7 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116803412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Smart-Tree: Neural Medial Axis Approximation of Point Clouds for 3D Tree Skeletonization Smart-Tree:用于3D树骨架化的点云的神经内轴线逼近

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2023-03-21 DOI: 10.48550/arXiv.2303.11560

Harry Dobbs, O. Batchelor, Richard D. Green, J. Atlas

引用次数: 0

A Study of Augmentation Methods for Handwritten Stenography Recognition 手写速记识别的增强方法研究

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2023-03-05 DOI: 10.48550/arXiv.2303.02761

R. Heil, Eva Breznik

引用次数: 1

Can representation learning for multimodal image registration be improved by supervision of intermediate layers? 多模态图像配准的表示学习能否通过中间层的监督得到改善?

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2023-03-01 DOI: 10.48550/arXiv.2303.00403

Elisabeth Wetzer, Joakim Lindblad, Natavsa Sladoje

{"title":"Can representation learning for multimodal image registration be improved by supervision of intermediate layers?","authors":"Elisabeth Wetzer, Joakim Lindblad, Natavsa Sladoje","doi":"10.48550/arXiv.2303.00403","DOIUrl":"https://doi.org/10.48550/arXiv.2303.00403","url":null,"abstract":"Multimodal imaging and correlative analysis typically require image alignment. Contrastive learning can generate representations of multimodal images, reducing the challenging task of multimodal image registration to a monomodal one. Previously, additional supervision on intermediate layers in contrastive learning has improved biomedical image classification. We evaluate if a similar approach improves representations learned for registration to boost registration performance. We explore three approaches to add contrastive supervision to the latent features of the bottleneck layer in the U-Nets encoding the multimodal images and evaluate three different critic functions. Our results show that representations learned without additional supervision on latent features perform best in the downstream task of registration on two public biomedical datasets. We investigate the performance drop by exploiting recent insights in contrastive learning in classification and self-supervised learning. We visualize the spatial relations of the learned representations by means of multidimensional scaling, and show that additional supervision on the bottleneck layer can lead to partial dimensional collapse of the intermediate embedding space.","PeriodicalId":319553,"journal":{"name":"Iberian Conference on Pattern Recognition and Image Analysis","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123242432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

MaxDropoutV2: An Improved Method to Drop out Neurons in Convolutional Neural Networks MaxDropoutV2:一种改进的卷积神经网络中丢弃神经元的方法

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2022-03-05 DOI: 10.48550/arXiv.2203.02740

C. F. G. Santos, Mateus Roder, L. A. Passos, J. P. Papa

引用次数: 0

An End-to-End Approach for Seam Carving Detection using Deep Neural Networks 基于深度神经网络的端到端焊缝雕刻检测方法

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2022-03-05 DOI: 10.48550/arXiv.2203.02728

Thierry Pinheiro Moreira, M. C. S. Santana, L. A. Passos, J. Papa, K. Costa

引用次数: 2

Learning Sparse Masks for Diffusion-based Image Inpainting 学习稀疏蒙版的扩散为基础的图像绘画

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2021-10-06 DOI: 10.1007/978-3-031-04881-4_42

Tobias Alt, Pascal Peter, J. Weickert

引用次数: 10

Improving Action Quality Assessment Using Weighted Aggregation 利用加权聚合改进行动质量评估

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2021-02-21 DOI: 10.1007/978-3-031-04881-4_46

Shafkat Farabi, H. Himel, Fakhruddin Gazzali, Md. Bakhtiar Hasan, M. H. Kabir, M. Farazi

引用次数: 3

Segmentation in Corridor Environments: Combining Floor and Ceiling Detection 走廊环境的分割:结合地板和天花板检测

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2019-07-01 DOI: 10.1007/978-3-030-31321-0_42

S. Lafuente-Arroyo, S. Maldonado-Bascón, H. Gómez-Moreno, C. Alén-Cordero

引用次数: 0

Characterization of Cardiac and Respiratory System of Healthy Subjects in Supine and Sitting Position 健康受试者仰卧位和坐位的心脏和呼吸系统特征

Iberian Conference on Pattern Recognition and Image Analysis Pub Date : 2019-07-01 DOI: 10.1007/978-3-030-31332-6_32

A. Ruiz, J. S. Mejía, J. M. López, B. Giraldo

引用次数: 1