Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 15 of 15 for “"RCNN"”.
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Depth aware RCNN
… detection branch in our model outperforms Faster-RCNN on the challenging KITTI detection benchmark and the Cityscapes dataset. Likewise, the performance of our depth prediction branch is slightly better compared with methods using the same depth prediction architecture.
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Multiple scale sharing faster-RCNN
The student, Siwei Tang, submitted this Thesis for approval on 2019-04-24 at 10:10.
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Region-based Convolutional Neural Network and Implementation of the Network Through Zedboard Zynq
… accurate. One version is the Region-based CNN (RCNN). This is our selected network design for a new implementation in an FPGA. This network identifies stop signs in an image. We successfully designed and trained an RCNN network in MATLAB and implemented it in the hardware to use in an embedded …
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Indoor navigation efficiency improvement in intelligent assistive systems (IAS) using neural networks
… using transfer learning of a pre-trained Mask-RCNN (Mask-Region based Convolutional Neural Network) because of the instance segmentation performed by Mask-RCNN. Pre-trained Mask-RCNN helps to produce different object combinations for different indoor home scenes. Another CNN is also developed, …
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Assessing High Dynamic Range Imagery Performance for Object Detection in Maritime Environments
… the performance of these networks. Faster-RCNN, SSD, and YOLOv5 were used to compare. Results determined Faster-RCNN and YOLOv5 networks trained on fixed exposure images outperformed their HDR counterparts while SSDs performed better when using HDR images. Better fixed exposure network …
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A Transfer Learning Approach for Automatic Mapping of Retrogressive Thaw Slumps (RTSs) in the Western Canadian Arctic
… learning methods. We employed a pre-trained Mask-RCNN model to automatically map RTSs on Banks Island and Victoria Island in the western Canadian Arctic, where there is extensive RTS activity. We tested the model with different settings, including image band combinations, backbones, and backbone …
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Talning fiska með tölvusjón
… Notast verður við tauganetin Yolo, Mask RCNN og Retinanet. Niðurstöður rannsóknarinnar sýna að þetta sé mögulegt með tauganetunum með mismunandi skekkju. Bakvið talningu fiska þarf meira en tauganet sem finnur fiska á mynd, en einnig þarf að búa til reiknirit sem fylgir hlutum á milli …
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Identification et détection du homard américain dans les secteurs de la pêche et de la transformation basées sur les systèmes de vision.
… été sélectionnés, tels que YOLOv3, YOLOv4, FasterRCNN, Mask-RCNN et YOLOv7. Ils ont été implémentés sur des plateformes embarquées de Nvidia. Pour cela, un ensemble de données spécifique aux homards a été construit et utilisé pour réentraîner ces modèles, en tirant parti de l'apprentissage par …
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Using Siamese neural networks to identify individual animals
… Convolution Neural Networks (Mask - RCNN) [He et al., 2017] are used for the object detection and instance segmentation which answers (1). This is a modern deep learning approach which has been used for tasks such as identifying breast cancer tumors [Chiao et al., 2019] outside of …
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A Real-Time 3D Object Detection, Recognition and Presentation System on a Mobile Device for Assistive Navigation
… 2D object detectors (e.g., YOLO, SSD, Mask RCNN) based on the requested task and requirements of the run time and details for the 3D detection result. It can run on a cloud server or mobile application. The object tracking and update module minimizes the computational power for long- term …
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A Knowledge Graph based Method on Language Understanding for Customer Service
… we explore a new model named <strong>Hierar-BERT-RCNN</strong> to recognize and classify vague question in hierarchical multi-label classification step. This model outperforms over hierarchical baseline models (BERT, BERT-CNN, BERT-DPCNN) on DuEE dataset on average 0.83% higher in main level and …
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End-To-End Text Detection Using Deep Learning
… followed by a deep network based on Faster-RCNN. The attention model produces a high-resolution map that indicates likely locations of text instances. A novel aspect of the system is an early fusion step that merges the attention map directly with the input image prior to word-box …
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A study on the effect of target object size in object detection
… of Region-based Convolutional Neural Networks (RCNN). Studies have been carried out to improve object detection models. However, the detection of small objects still poses numerous challenges for the said models. Small object detection is considered as one of the biggest challenges in object …
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A Context Aware Classification System for Monitoring Driver’s Distraction Levels
… Recurrent Convolutional Neural Network (Fast-RCNN) architecture addresses the physiological attributes. Secondly, a novel two-tier FRCNN-LSTM framework is devised to classify the severity of driver distraction. Thirdly, a Dynamic Bayesian Network (DBN) for the prediction of driver distraction. …
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Computer vision based classification of fruits and vegetables for self-checkout at supermarkets
The field of machine learning, and, in particular, methods to improve the capability of machines to perform a wider variety of generalised tasks are among the most rapidly growing research areas in today’s world. The current applications of machine learning and artificial intelligence can be …