Results 221 to 230 of about 16,805 (257)

Nuclei R-CNN: Improve Mask R-CNN for Nuclei Segmentation

2019 IEEE 2nd International Conference on Information Communication and Signal Processing (ICICSP), 2019
Accurate nuclei segmentation plays an essential role in medical research and various clinical applications. Recently, deep learning has demonstrated its superior performance on object segmentation in natural scene images. However, these methods cannot produce fine segmentation in histopathological images.
Guofeng Lv, Ke Wen, Zheng Wu, Xu Jin, Hong An, Jie He   +5 more
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Deep Learning Techniques—R-CNN to Mask R-CNN: A Survey

2019
With the advances in the field of machine learning, statistics, and computer vision, the advanced deep learning techniques have attracted increasing research interests over the last decade. This is because of their inherent capabilities of overcoming the drawback of traditional techniques.
Puja Bharati, Ankita Pramanik
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Design of a Deep Face Detector by Mask R-CNN

2019 27th Signal Processing and Communications Applications Conference (SIU), 2019
In this work an existing object detector, Mask RCNN, is trained for face detection and performance results are reported by using the learned model. Differing from the existing work, it is aimed to train the deep detector with a small number of training examples and also to perform instance segmentation along with an object bounding box detection ...
Ozan Cakiroglu, Caner Ozer, Bilge Günsel   +2 more
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Inshore Ship Detection Based on Mask R-CNN

IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
Inshore ship detection is a popular research domain for optical remote sensing image understanding with many applications in harbor management. However, recent approaches on inshore ship detection depend heavily on hand-crafted features, which need a complicated procedure.
Shanlan Nie, Zhiguo Jiang 0001, Haopeng Zhang 0001, Bowen Cai 0001, Yuan Yao   +4 more
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Automatic Crack Detection using Mask R-CNN

2019 11th International Symposium on Image and Signal Processing and Analysis (ISPA), 2019
In order to avoid possible failures and prevent damage in civil infrastructures, such as tunnels and bridges, inspection should be done on a regular basis. Cracks are one of the earliest indications of degradation, hence, their detection allows preventive measures to be taken to avoid further damage. In this paper, we demonstrate that Mask R-CNN can be
Leanne Attard, Carl James Debono, Gianluca Valentino, Mario Di Castro, Alessandro Masi, Luigi Scibile   +5 more
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Ball Detection Using Yolo and Mask R-CNN

2018 International Conference on Computational Science and Computational Intelligence (CSCI), 2018
Many computer vision applications rely on accurate and fast object detection, and in our case, ball detection serves as a prerequisite for action recognition in handball scenes. We compare the performance of two of the state-of- the-art convolutional neural network-based object detectors for the task of ball detection in non-staged, real-world ...
Pobar, Miran, Ivašić-Kos, Marina, Burić, Matija   +2 more
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Object Dimension Measurement Based on Mask R-CNN

2019
An object dimension measurement system based on Mask R-CNN and monocular vision is introduced to perform non-contact measurement of the two-dimensional size of objects in irregular shape. Firstly, Mask R-CNN is used for detecting all objects to be measured and segmenting each object from the image captured by the camera.
Zuo Wei, Bin Zhang 0022, Pei Liu
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Radio Galaxy Morphology Classification with Mask R-CNN

Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing, 2020
Due to the sheer scale of data generated from newer radio galaxy surveys, automating the classification of radio galaxy morphologies has become an active area of study in recent years. One promising solution is CLARAN: A proof-of-concept radio source morphology classifier based upon the Faster Region-based Convolutional Neural Network (Fast R-CNN ...
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Solar Filament Detection using Mask R-CNN

2019 International Workshop on Big Data and Information Security (IWBIS), 2019
Many algorithms have been proposed to detect solar filaments from H-Alpha images automatically, most of them use intensity thresholding method which requires intensity normalization. We propose a fast, automatic, and efficient method to detect filaments on H-Alpha images without carrying out intensity normalization using Mask R-CNN. The proposed method
Rian Pramudia Salasa, Aniati Murni Arymurthy   +1 more
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Mask R-CNN assisted diagnosis of spinal tuberculosis

Journal of X-Ray Science and Technology
The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to misdiagnosis and delays in treatment progress but also contributes to the continued transmission of tuberculosis bacteria, posing a risk to other individuals.
Wenjun Li, Yanfan Li, Huan Peng, Weijun Liang   +3 more
openaire   +2 more sources