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Detecting Advertising Materials via Multi-Scale Instance Segmentation Network

Ben Xu, Chun Yang, Hongfa Wang, Xiaobin Zhu, Xu-Cheng Yin
2019 Australian Journal of Intelligent Information Processing Systems  
Secondly, ASPP module and multi-scale prediction structure are introduced to handle materials with various scales.  ...  In our work, we firstly adopt a fully convolutional instance segmentation network to capture the semantic information and link information of pixels.  ...  In this paper, we design a multi-scale instance segmentation network (MSISN) to address advertising materials detection task.  ... 
dblp:journals/ajiips/XuYWZY19 fatcat:7xfgnn5hfjdhvazmaptzdokppa

Temporal Fusion Based Mutli-scale Semantic Segmentation for Detecting Concealed Baggage Threats [article]

Muhammed Shafay and Taimur Hassan and Ernesto Damiani and Naoufel Werghi
2021 arXiv   pre-print
To address this, we present a novel temporal fusion driven multi-scale residual fashioned encoder-decoder that takes series of consecutive scans as input and fuses them to generate distinct feature representations  ...  Detection of illegal and threatening items in baggage is one of the utmost security concern nowadays. Even for experienced security personnel, manual detection is a time-consuming and stressful task.  ...  Also, the problem of baggage threat detection is also addressed via semantic segmentation [4] and instance segmentation [5] approaches.  ... 
arXiv:2111.02651v2 fatcat:ufeivmaervabbjhfjyeu6bn6tm

Industrial Scene Text Detection with Refined Feature-attentive Network [article]

Tongkun Guan, Chaochen Gu, Changsheng Lu, Jingzheng Tu, Qi Feng, Kaijie Wu, Xinping Guan
2021 arXiv   pre-print
Specifically, we design a parallel feature integration mechanism to construct an adaptive feature representation from multi-resolution features, which enhances the perception of multi-scale texts at each  ...  scale-specific level to generate a high-quality attention map.  ...  Overall Pipeline Our network mainly includes four parts: a ResNet-FPN backbone for extracting multi-scale features, a detection branch of classification and regression tasks, a semantic segmentation branch  ... 
arXiv:2110.12663v1 fatcat:kfskmludrrccphhigsc7fepwki

Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers [article]

Raphaël Barman, Maud Ehrmann, Simon Clematide, Sofia Ares Oliveira, Frédéric Kaplan
2020 arXiv   pre-print
Results show consistent improvement of multimodal models in comparison to a strong visual baseline, as well as better robustness to high material variance.  ...  others, the use of finer-grained segmentation typologies and the consideration of complex, heterogeneous documents such as historical newspapers.  ...  On the other side of the spectrum, another line of research performs newspaper content segmentation using text only (usually when images are not available) via the detection of homogeneous passages based  ... 
arXiv:2002.06144v4 fatcat:43kx7oyorbaqrbni4gvqeetygy

Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers

Barman, Ehrmann, Clematide, Ares Oliveira, Kaplan
2021 Zenodo  
Results show consistent improvement of multimodal models in comparison to a strong visual baseline, as well as better robustness to the wide variety of our material.  ...  , among others, the use of more fine-grained segmentation typologies and the consideration of complex, heterogeneous documents such as historical newspapers.  ...  On the other side of the spectrum, another line of research performs newspaper content segmentation using text only (usually when images are not available) via the detection of homogeneous passages based  ... 
doi:10.5281/zenodo.4065270 fatcat:zwymvcvxofb3fpwgasmvo54r6i

Exploiting Multi-Layer Grid Maps for Surround-View Semantic Segmentation of Sparse LiDAR Data [article]

Frank Bieder, Sascha Wirges, Johannes Janosovits, Sven Richter, Zheyuan Wang, Christoph Stiller
2020 arXiv   pre-print
We compare single-layer and multi-layer approaches and demonstrate the benefit of a multi-layer grid map input.  ...  This method allows us to evaluate and compare the performance of our models not only based on grid cells with a detection, but on the full visible measurement range.  ...  Their Feature Pyramid Network (FPN) adds features via 1x1 convolutions from the top-down path to features from the bottom-up path and is a common structure for many semantic segmentation and object detection  ... 
arXiv:2005.06667v1 fatcat:horxaclekfadtkzdqlcrz6witm

Learning Neural Textual Representations for Citation Recommendation

Binh Thanh Kieu, Inigo Jauregi Unanue, Son Bao Pham, Hieu Xuan Phan, Massimo Piccardi
2021 2020 25th International Conference on Pattern Recognition (ICPR)  
Operation for Multi-Scale Feature Learning in Semantic Segmentation DAY 3 -Jan 14, 2021 Fang, Fen; Xu, Qianli; Li, Liyuan; Gu, Ying; Lim, Joo-Hwee 1983 Detecting Objects with High Object Region  ...  2021 Shin, Beomjo; Cho, Junsu; Yu, Hwanjo; Choi, Seungjin 1148 Sparse Network Inversion for Key Instance Detection in Multiple Instance Learning DAY 2 -Jan 13, 2021 Jung, Jay Hoon; Kwon, YoungMin  ... 
doi:10.1109/icpr48806.2021.9412725 fatcat:3vge2tpd2zf7jcv5btcixnaikm

SSD vs. YOLO for Detection of Outdoor Urban Advertising Panels under Multiple Variabilities

Ángel Morera, Ángel Sánchez, A. Belén Moreno, Ángel D. Sappa, José F. Vélez
2020 Sensors  
Finally, a comparison of the two analyzed object detection models with different types of semantic segmentation networks and using the same evaluation metrics is also included.  ...  This work compares Single Shot MultiBox Detector (SSD) and You Only Look Once (YOLO) deep neural networks for the outdoor advertisement panel detection problem by handling multiple and combined variabilities  ...  Multi-resolution techniques allow detecting objects at several scales and at different layers of the network.  ... 
doi:10.3390/s20164587 pmid:32824232 fatcat:rlqkcduq6vgyrdakidm64weg4e

Weakly Supervised Deep Learning for COVID-19 Infection Detection and Classification from CT Images

Shaoping Hu, Yuan Gao, Zhangming Niu, Yinghui Jiang, Lao Li, Xianglu Xiao, Minhao Wang, Evandro Fei Fang, Wade Menpes-Smith, Jun Xia, Hui Ye, Guang Yang
2020 IEEE Access  
Loosely inspired by [22] , we proposed a multi-view U-Net [23] based segmentation network for lung segmentation.  ...  FIGURE 1 . 1 Network architecture of our proposed weakly supervised multi-scale learning framework for COVID-19/NP/CAP classification and lesions detection.  ...  the sixth place in the IEEE ICME Grand Challenge AI competition 2019, and the winner of the Tencent Advertising Algorithm AI competition 2019.  ... 
doi:10.1109/access.2020.3005510 fatcat:e5yppav35rectbwqkiiuy7gr4i

Segmentation-Renormalized Deep Feature Modulation for Unpaired Image Harmonization [article]

Mengwei Ren, Neel Dey, James Fishbaugh, Guido Gerig
2021 arXiv   pre-print
Deep networks are now ubiquitous in large-scale multi-center imaging studies.  ...  We replace the affine transformations used in the normalization layers within generative networks with trainable scale and shift parameters conditioned on jointly learned anatomical segmentation embeddings  ...  Current work has sought to improve translation quality and robustness via multi-task strategies. For instance, translation ©2021 IEEE. Personal use of this material is permitted.  ... 
arXiv:2102.06315v2 fatcat:lozfvb5cpnbq7ixrade7zou36e

The DComp Testbed

Ryan Goodfellow, Stephen Schwab, Erik Kline, Lincoln Thurlow, Geoff Lawler
2019 USENIX Security Symposium  
Adopting EVPN routing, DCompTB employs a flexible and highly adaptable strategy to provision network emulation and infrastructure services on a per-experiment basis.  ...  The DComp Testbed effort has built a large-scale testbed, combining customized nodes and commodity switches with modular software to launch the Merge open source testbed ecosystem.  ...  Acknowledgements This material is based upon work supported by Defense Advanced Research Projects Agency (DARPA) under Contract No. HR001117C0053.  ... 
dblp:conf/uss/GoodfellowSKTL19 fatcat:xqad6tfcsjgzxgghvmkblrmey4

Simultaneous Nuclear Instance and Layer Segmentation in Oral Epithelial Dysplasia [article]

Adam J. Shephard, Simon Graham, R.M. Saad Bashir, Mostafa Jahanifar, Hanya Mahmood, Syed Ali Khurram, Nasir M. Rajpoot
2021 arXiv   pre-print
The proposed architecture consists of an encoder branch and four decoder branches for simultaneous instance segmentation of nuclei and semantic segmentation of the epithelial layers.  ...  To the best of our knowledge, ours is the first method for simultaneous nuclear instance segmentation and semantic tissue segmentation, with potential for use in computational pathology for other similar  ...  Acknowledgements This work was supported by a Cancer Research UK Early Detection Project Grant, as part of the ANTICIPATE study.  ... 
arXiv:2108.13904v2 fatcat:3igjlqihrrfnlbyjcuj6qakhvu

Weakly Supervised Adversarial Domain Adaptation for Semantic Segmentation in Urban Scenes

Qi Wang, Junyu Gao, Xuelong Li
2019 IEEE Transactions on Image Processing  
To be specific, a detection and segmentation ("DS" for short) model focuses on detecting objects and predicting segmentation map; a pixel-level domain classifier ("PDC" for short) tries to distinguish  ...  Semantic segmentation, a pixel-level vision task, is developed rapidly by using convolutional neural networks (CNNs).  ...  [26] propose a supervised multi-task learning for instance segmentation, which does not segment the background objects. Wang et al.  ... 
doi:10.1109/tip.2019.2910667 fatcat:rjt76jkqmjajxcubmdlcyws36e

Digital reality: a model-based approach to supervised learning from synthetic data

Tim Dahmen, Patrick Trampert, Faysal Boughorbel, Janis Sprenger, Matthias Klusch, Klaus Fischer, Christian Kübel, Philipp Slusallek
2019 AI Perspectives  
Hierarchical neural networks with large numbers of layers are the state of the art for most computer vision problems including image classification, multi-object detection and semantic segmentation.  ...  We propose the Digital Reality concept and demonstrate its potential in different application domains, including industrial inspection, autonomous driving, smart grid, and microscopy research in material  ...  For multi-object detection networks, image space bounding box information can be generated trivially from the object ID images.  ... 
doi:10.1186/s42467-019-0002-0 fatcat:p4ttyucarfabfjhpvp56gvex2i

Front Matter: Volume 9791

2016 Medical Imaging 2016: Digital Pathology  
Please use the following format to cite material from these proceedings: Publication of record for individual papers is online in the SPIE Digital Library.  ...  of a fully automated quantitative framework for characterizing general breast tissue histology via color histogram and color texture analysis [9791-9] DETECTION AND SEGMENTATION 9791 0B Hotspot  ...  Other copying for republication, resale, advertising or promotion, or any form of systematic or multiple reproduction of any material in this book is prohibited except with permission in writing from the  ... 
doi:10.1117/12.2240781 dblp:conf/midp/X16 fatcat:5t2qw4ofb5h4xjg4xxhhyoan7m
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