Lightweight Ship Detection Methods Based on YOLOv3 and DenseNet
نویسندگان
چکیده
منابع مشابه
JPEG Steganalysis Based on DenseNet
Current research has indicated that convolution neural networks (CNNs) can work well for steganalysis in the spatial domain. There are, however, fewer works based on CNN in the JPEG domain. In this paper, we have proposed a 32layer CNN architecture that is based on Dense Convolutional Network (DenseNet) for JPEG steganalysis. The proposed CNN architecture can reuse features by concatenating fea...
متن کاملislanding detection methods for microgrids
امروزه استفاده از منابع انرژی پراکنده کاربرد وسیعی یافته است . اگر چه این منابع بسیاری از مشکلات شبکه را حل می کنند اما زیاد شدن آنها مسائل فراوانی برای سیستم قدرت به همراه دارد . استفاده از میکروشبکه راه حلی است که علاوه بر استفاده از مزایای منابع انرژی پراکنده برخی از مشکلات ایجاد شده توسط آنها را نیز منتفی می کند . همچنین میکروشبکه ها کیفیت برق و قابلیت اطمینان تامین انرژی مشترکان را افزایش ...
15 صفحه اولA Novel Algorithm for Automatic Ship and Oil Spill Detection Based on Time-frequency Methods
A novel method for automatic ship detection based on the Wavelet Transform (WT) has been recently presented. The results obtained point out the potential of the use of a multiresolution time-frequency framework for the analysis of SAR imagery. On the one hand, this paper aims at reviewing the algorithm for automatic spot detection on speckled images. On the other hand, a novel algorithm for the...
متن کاملLog-DenseNet: How to Sparsify a DenseNet
Skip connections are increasingly utilized by deep neural networks to improve accuracy and cost-efficiency. In particular, the recent DenseNet is efficient in computation and parameters, and achieves state-of-the-art predictions by directly connecting each feature layer to all previous ones. However, DenseNet’s extreme connectivity pattern may hinder its scalability to high depths, and in appli...
متن کاملSimulation-Based Radar Detection Methods
In this paper, radar detection based on Monte Carlo sampling is studied. Two detectors based on Importance Sampling are presented. In these detectors, called Particle Detector, the approximated likelihood ratio is calculated by Monte Carlo sampling. In the first detector, the unknown parameters are first estimated and are substituted in the likelihood ratio (like the GLRT method). In the sec...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2020
ISSN: 1563-5147,1024-123X
DOI: 10.1155/2020/4813183