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Showing 1 to 17 of 17 for “"mobilenet"”.
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Towards On-Device Detection of Sharks with Drones
… resource constraints. To this end we look at SSD MobileNet, a popular object detection architecture that targets edge devices by sacrificing some accuracy. We look at the results of SSD MobileNet in detecting sharks from a data set of aerial images created by a collaboration between Cal Poly and …
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Slimmable neural networks for edge devices
… than) that of individually trained models of MobileNet v1, MobileNet v2, ShuffleNet and ResNet-50 at different widths. We also demonstrate better performance of slimmable models compared with individual ones across a wide range of applications including COCO bounding-box object detection, …
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Low-cost deep learning UAV and Raspberry Pi solution to real time pavement condition assessment
… real-time object detection architecture SSD with MobileNet feature extractor is the best combination for real-time defect detection to be used by tiny computers. A low-cost Raspberry Pi smart defect detector camera was configured using the trained SSD MobileNet v1, which can be deployed with UAV …
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Personalized Voice Activated Grasping System for a Robotic Exoskeleton Glove
… simultaneously. The system uses MobileNet as the feature extractor to reduce computational cost. The HMI is tuned to allow better performance in grasping daily objects. This study focuses on applying the CVASV HMI to the exoskeleton glove to perform a stable grasp with …
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Investigating automated bird detection from webcams using machine learning
… (SSD) and Faster R-CNN in combination with MobileNet-V2, ResNet50, ResNet101, ResNet152, and Inception ResNet-V2 feature extractors were studied and evaluated. Through the use of transfer learning, all the models were initialized using weights pre-trained on the MS COCO (Microsoft Common …
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Computer-assisted Workflow Recognition for Central Venous Catheterization
… two different networks, Inception-V3 and MobileNet, and compared their accuracy to the initial color-based approach. Results: Central Line Tutor was designed, implemented, and tested. The system was able to successfully recognize all tasks in the central venous catheterization workflow …
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Neural network simplification using a progressive barrier based approach
… trade-offs on a highly compact MobileNet architecture, compared with state-of-the-art automated network simplification approaches. For image classification on the ImageNet dataset, the algorithm reduces the number of multiply-accumulate operations by 1.68x while achieving 0.9% …
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Energy-aware DNN Quantization for Processing-In-Memory Architecture
… several DNN models VGG-19, ResNet-18, ResNet-50, MobileNet-V2, and SqueezeNet. Also, the area, dynamic energy, and energy efficiency in the compressed models with various memory technologies are analyzed. EGQ shows 15%-103% higher energy efficiency with 2% accuracy loss than other PIM-aware …
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Embedded object detection and position estimation for RoboCup Small Size League
… the input. In the object detection dataset, the MobileNet v1 SSD achieves 44.88% AP for the three detected classes at 94 Frames Per Second (FPS) while running on a SSL robot. And the position estimator for a detected ball achieves a Root Mean Square Error (RMSE) of 34.88mm.
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Terrain characterization for site selection and preparation
… Segnet) and three base models (VGG, ResNet, and MobileNet) were modified to include multispectral imagery and compared. Seven land cover classes were determined with an accuracy of 82.71% by model ResNet/SegNet. To determine soil moisture content (SMC), ten models were developed to predict soil …
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Application of unmanned aerial systems and deep learning in high-throughput plant phenotyping
… panicles; 2) to assess the application of MobileNet and CenterNet models in cotton stand counting at the seedling stage; 3) to develop an algorithm for detecting and counting open cotton bolls and assess the performance in relation to image acquisition altitudes and camera angles; 4) to …
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A framework for an early warning system for the management of the spread of locust invasion based on artificial intelligence technologies.
… Neural Network (CNN) model, specifically the MobileNet version 2 quantized model, tailored for automatic identification of locust species. This model achieved an average precision rate of 91% for Locusta migratoria and 85% for Nomadacris septemfasciata using a custom dataset of 1700 images …
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Detection of Texture-less Occluded Objects Using Deep Convolutional Neural Networks
… (Faster R-CNN) to accomplish the main objective. Mobilenet is the base i model in SSD; whereas, Inception is the base model in Faster R-CNN. SSD is superior than Faster R-CNN in terms of speed, but inferior in terms of average precision. A large number of training samples are required in SSD to …
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Bone age estimation using machine learning approach: An assessment using hand and wrist bones of South African children
… the pretrained models, Xception, InceptionV3, MobileNet, and VGG-16, using the pre-processed and unprocessed datasets and comparing their performance. The pre-processed dataset was selected for model benchmarking to find the best-performing model for bone age estimation out of the four …
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Cross-layer methods for energy-efficient inference using in-memory architectures
… methods on compact networks such as MobileNet-V1. Next, a compositional framework is proposed that can be used to relate the energy consumption and SNR of in-memory architectures to the various circuit, architectural, and algorithmic parameters. Analysis using this framework will …
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The sorting hat: An automated activity index based on finishing pig behavior
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2027-05-01
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Deep Multimodal Physiological Learning of Cerebral Vasoregulation Dynamics on Stroke Patients Towards Precision Brain Medicine
… Walk dataset from the PhysioNet website. CNN and MobileNetV3 are employed in classification purposes of these signals, attempting to iden tify cerebral health. The accuracy of the model and robustness of these methods is greatly enhanced when multiple signals are integrated. Overall, this study …