Results 171 to 180 of about 487,056 (216)
Some of the next articles are maybe not open access.
Faster R-CNN based microscopic cell detection
2017 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2017The automatic analysis of microscopic images is an important subject of medical image processing, of which the cell detection is an important part. However, owing to the different size and shape, as also as the adhesion among cells, detecting and locating cells accurately seems to be a very challenging task.
Su Yang +5 more
openaire +1 more source
GlioMeNet: Brain tumor analysis using faster R-CNN
2021 2nd Global Conference for Advancement in Technology (GCAT), 2021Beyond the advancement in the medical field, the development in the neuroradiology to diagnose the pathology of the brain tumor is still a concern for the neuron experts. To get over the formal problem, the Deep learning technique which is the sub domain of AI [Artificial Intelligence] is availed. Deep structured learning has the ability to analyze the
G Sethuram Rao, D Vydeki
openaire +1 more source
2.5D Faster R-CNN for Distance Estimation
2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2018Estimating the distance of a target object from a single image is a challenging task since a large variation in the object appearance makes the regression of the distance difficult. In this paper, to tackle such the challenge, we propose 2.5D anchors which provide good candidates of distances, based on a perspective camera model.
Hirotaka Hachiya +4 more
openaire +1 more source
Squeeze and Excitation Rank Faster R-CNN for Ship Detection in SAR Images
IEEE Geoscience and Remote Sensing Letters, 2019Synthetic aperture radar (SAR) ship detection is an important part of marine monitoring. With the development in computer vision, deep learning has been used for ship detection in SAR images such as the faster region-based convolutional neural network (R-
Zhao Lin +3 more
semanticscholar +1 more source
Pig Breed Detection Using Faster R-CNN
2020In this paper, convolutional neural network object detection technology has been used to detect pig breeds with high precision from images captured through mobile cameras. The pretrained model is retrained on several images of 6 different pure breed pigs obtained from organized farms. The Faster R-CNN Inception-ResNet-v2 model has been used in transfer
Pritam Ghosh +5 more
openaire +1 more source
Minutiae Points Extraction Using Faster R-CNN
2020A fingerprint is an impression of the friction ridges of all parts of the finger and it is a widely used biometric trait. In a fingerprint authentication system, minutiae points are used as features to authenticate an individual. There are many traditional techniques which have been proposed to extract minutiae points from a fingerprint.
Vivek Singh Baghel +3 more
openaire +1 more source
Garbage Classification using Faster R-CNN
2023 International Conference on Electrical and Information Technology (IEIT), 2023Puteri Nurul Ma’Rifah +2 more
openaire +1 more source
CAPTCHA Recognition Based on Faster R-CNN
2017In this paper, Faster R-CNN was employed to recognize the CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart). Unlike traditional method, the proposed method is based on deep learning object detection framework. By inputting the database into the network and training the Faster R-CNN, the feature map can be obtained ...
Feng-Lin Du +5 more
openaire +1 more source
An accurate object detection of wood defects using an improved Faster R-CNN model
Wood Material Science & EngineeringWood defect classification and location are crucial for automatic repair and reuse in wood product manufacture, which requires high accuracy and efficiency in the engineering practice.
Xianghe Zou +4 more
semanticscholar +1 more source