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ESTAN: Enhanced Small Tumor-Aware Network for Breast Ultrasound Image Segmentation [article]

Bryar Shareef, Alex Vakanski, Min Xian, Phoebe E. Freer
2020 arXiv   pre-print
Breast tumor segmentation is a critical task in computer-aided diagnosis (CAD) systems for breast cancer detection because accurate tumor size, shape and location are important for further tumor quantification  ...  In this paper, we propose a novel deep neural network architecture, namely Enhanced Small Tumor-Aware Network (ESTAN), to accurately and robustly segment breast tumors.  ...  [20] proposed an augmented technique for the R-CNN algorithm with a context model and small region proposal generator; which was the first benchmark dataset for small object detection.  ... 
arXiv:2009.12894v1 fatcat:dudddq2nmzdt7gkq2bpiyv2yfu

Fine-Context Shadow Detection using Shadow Removal [article]

Jeya Maria Jose Valanarasu, Vishal M. Patel
2021 arXiv   pre-print
First, we propose a Fine Context-aware Shadow Detection Network (FCSD-Net), where we constraint the receptive field size and focus on low-level features to learn fine context features better.  ...  To make use of this complementary nature of shadow detection and removal tasks, we train an auxiliary network for shadow removal and propose a complementary feature learning block (CFL) to learn and fuse  ...  [15] explored a direction-aware manner to analyze image context for shadow detection.  ... 
arXiv:2109.09609v2 fatcat:v2tmamsmyjho5ergimxumah5gq

Stan: Small tumor-aware network for breast ultrasound image segmentation [article]

Bryar Shareef, Min Xian, Aleksandar Vakanski
2020 arXiv   pre-print
In this paper, we propose a novel deep learning architecture called Small Tumor-Aware Network (STAN), to improve the performance of segmenting tumors with different size.  ...  The capacity to detecting small tumors is particularly important in finding early stage cancers using computer-aided diagnosis (CAD) systems.  ...  To overcome this problem, we propose the Small Tumor-Aware Network (STAN) to extract and fuse image context information at different scales.  ... 
arXiv:2002.01034v1 fatcat:vmy5hfg3yvg6vaf4hba37lsebq

TB-Net: A Three-Stream Boundary-Aware Network for Fine-Grained Pavement Disease Segmentation [article]

Yujia Zhang, Qianzhong Li, Xiaoguang Zhao, Min Tan
2020 arXiv   pre-print
To this end, we propose a three-stream boundary-aware network (TB-Net).  ...  Existing methods mainly address the tasks of crack detection and segmentation that are only tailored for long-thin crack disease.  ...  Results of the ablation experiments for analyzing the effect of the context-aware attention module. We compare our TB-Net to the model that does not make use of the context-aware attention module.  ... 
arXiv:2011.03703v1 fatcat:stfwqimr25c57gvfz7e4qctzke

Global Context-Aware-Based Deformable Residual Network Module for Precise Pest Recognition and Detection

Lin Jiao, Gaoqiang Li, Peng Chen, Rujing Wang, Jianming Du, Haiyun Liu, Shifeng Dong
2022 Frontiers in Plant Science  
The detection method adopts a deformable residual network to extract pest features and a global context-aware module for obtaining region-of-interests of agricultural pests.  ...  The detection results of the proposed method are compared with the detection results of other state-of-the-art methods, for example, RetinaNet, YOLO, SSD, FPN, and Cascade RCNN modules.  ...  Generally, low-level features are beneficial for the detection of small objects.  ... 
doi:10.3389/fpls.2022.895944 pmid:35720529 pmcid:PMC9201688 fatcat:ku32czhnp5fy3nwvj6icppqb7q

ACNet: Mask-Aware Attention with Dynamic Context Enhancement for Robust Acne Detection [article]

Kyungseo Min, Gun-Hee Lee, Seong-Whan Lee
2021 arXiv   pre-print
Finally, Mask-Aware Multi-Attention detects densely arranged and small acne by suppressing uninformative regions and highlighting probable acne regions.  ...  To address these problems, we propose an acne detection network which consists of three components, specifically: Composite Feature Refinement, Dynamic Context Enhancement, and Mask-Aware Multi-Attention  ...  Third, Mask-Aware Multi-Attention suppresses noise and highlights object cues for densely distributed and small acne detection.  ... 
arXiv:2105.14891v3 fatcat:j64nn46o4zgcbisezorz6wiuze

ℱ3-Net: Feature Fusion and Filtration Network for Object Detection in Optical Remote Sensing Images

Xinhai Ye, Fengchao Xiong, Jianfeng Lu, Jun Zhou, Yuntao Qian
2020 Remote Sensing  
As a result, more relevant and accurate context information is extracted for further detection.  ...  Object detection in remote sensing (RS) images is a challenging task due to the difficulties of small size, varied appearance, and complex background.  ...  [15] proposed a context-aware detection network (CAD-Net) to integrate scene-level global semantics and object-level local contexts of objects for more consideration of low-contrast objects.  ... 
doi:10.3390/rs12244027 fatcat:jxhuwbvyx5fblkdkqpq55zjauu

COMET: Context-Aware IoU-Guided Network for Small Object Tracking [article]

Seyed Mojtaba Marvasti-Zadeh, Javad Khaghani, Hossein Ghanei-Yakhdan, Shohreh Kasaei, Li Cheng
2020 arXiv   pre-print
To address this problem, we introduce a context-aware IoU-guided tracker (COMET) that exploits a multitask two-stream network and an offline reference proposal generation strategy.  ...  Empirically, COMET outperforms the state-of-the-arts in a range of aerial view datasets that focusing on tracking small objects.  ...  Motivated by the issues and also recent advances in small object detection, this paper proposes a Context-aware iOu-guided network for sMall objEct Tracking (COMET).  ... 
arXiv:2006.02597v3 fatcat:m2jmlmdryvbplfv6xkhgm6jxzi

Scale-Aware Trident Networks for Object Detection [article]

Yanghao Li, Yuntao Chen, Naiyan Wang, Zhaoxiang Zhang
2019 arXiv   pre-print
Then, we adopt a scale-aware training scheme to specialize each branch by sampling object instances of proper scales for training.  ...  In this work, we first present a controlled experiment to investigate the effect of receptive fields for scale variation in object detection.  ...  for object detection.  ... 
arXiv:1901.01892v2 fatcat:mb5n2jo5zngoxbspmba4oydnha

SAC-Net: Spatial Attenuation Context for Salient Object Detection [article]

Xiaowei Hu, Chi-Wing Fu, Lei Zhu, Tianyu Wang, Pheng-Ann Heng
2020 arXiv   pre-print
By further embedding the module to process individual layers in a deep network, namely SAC-Net, we can train the network end-to-end and optimize the context features for detecting salient objects.  ...  This paper presents a new deep neural network design for salient object detection by maximizing the integration of local and global image context within, around, and beyond the salient objects.  ...  Moreover, we compare the time performance of our SAC-Net with other methods for salient object detection.  ... 
arXiv:1903.10152v3 fatcat:rfd5v5basjgl7fqs7rqoupt7fy

EM-NET: Centerline-Aware Mitochondria Segmentation in EM Images via Hierarchical View-Ensemble Convolutional Network [article]

Zhimin Yuan, Jiajin Yi, Zhengrong Luo, Zhongdao Jia, Jialin Peng
2020 arXiv   pre-print
To address these problems, we introduce a multi-task network named EM-Net, which includes an auxiliary centerline detection task to account for shape information of mitochondria represented by centerline  ...  Therefore, the centerline detection sub-network is able to enhance the accuracy and robustness of segmentation task, especially when only a small set of annotated data are available.  ...  The performance of both our method and 3D U-Net are superior than the 2D U-Net, which further confirms the importance of 3D spatial context.  ... 
arXiv:1912.00201v3 fatcat:o6r3a32jdbeojeslks27aclmaq

Camouflaged Object Detection via Context-aware Cross-level Fusion [article]

Geng Chen, Si-Jie Liu, Yu-Jia Sun, Ge-Peng Ji, Ya-Feng Wu, Tao Zhou
2022 arXiv   pre-print
To address these challenges, we propose a novel Context-aware Cross-level Fusion Network (C2F-Net), which fuses context-aware cross-level features for accurately identifying camouflaged objects.  ...  Camouflaged object detection (COD) aims to identify the objects that conceal themselves in natural scenes.  ...  For the small polyps, C 2 F-Net can accurately detect boundaries, while UNet [48] and UNet++ [68] fail.  ... 
arXiv:2207.13362v1 fatcat:vz5zdjbzpvd7da5a2lwdzq2anm

Density-Aware Convolutional Networks with Context Encoding for Airborne LiDAR Point Cloud Classification [article]

Xiang Li, Mingyang Wang, Congcong Wen, Lingjing Wang, Nan Zhou, Yi Fang
2019 arXiv   pre-print
In addition, to regularize the global semantic context, we implemented a context encoding module to predict a global context encoding and formulated a context encoding regularizer to enforce the predicted  ...  Experiments on the International Society for Photogrammetry and Remote Sensing (ISPRS) 3D labeling benchmark demonstrated the superiority of the proposed method for point cloud classification.  ...  ACKNOWLEDGMENTS We would like to gratefully acknowledge the ISPRS for providing airborne LiDAR data.  ... 
arXiv:1910.05909v1 fatcat:pfozwk24nbhzpjc3smjcusoc6i

AWEU-Net: An Attention-Aware Weight Excitation U-Net for Lung Nodule Segmentation

Syeda Furruka Banu, Md. Mostafa Kamal Sarker, Mohamed Abdel-Nasser, Domenec Puig, Hatem A. Raswan
2021 Applied Sciences  
Accurate lung nodule detection and segmentation in computed tomography (CT) images is a vital step for diagnosing lung cancer early.  ...  with two effective blocks, namely position attention-aware weight excitation (PAWE) and channel attention-aware weight excitation (CAWE), to enhance the ability to discriminate between nodule and non-nodule  ...  As shown, the Optimized Faster R-CNN model is able to detect the nodule regions, even for small nodules.  ... 
doi:10.3390/app112110132 fatcat:ohptudd47ffldp5o65a77w4v6i

A Mask Attention Interaction and Scale Enhancement Network for SAR Ship Instance Segmentation [article]

Tianwen Zhang, Xiaoling Zhang
2022 arXiv   pre-print
, and a global context block (GCB) to refine features.  ...  SE uses a content-aware reassembly of features block (CARAFEB) to generate an extra pyramid bottom-level to boost small ship performance, a feature balance operation (FBO) to improve scale feature description  ...  For better multi-scale performance, based on FPN [22] , SE employs a content-aware reassembly of features block (CARAFEB) to generate an extra pyramid bottom-level to enhance small ship performance, a  ... 
arXiv:2207.03912v1 fatcat:hvvlcaiavnfhhkqn4g7qeic5ie
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