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Classification in remote sensing, similar to semantic segmentation in computer vision, is aimed to assign a label to each pixel in images to indicate which class it belongs to. Fully convolutional networks (FCN), one of semantic segmentation methods, is proposed to tackle this problem in fully PolSAR images in this paper. To exploit the polarimetric information in PolSAR images, H-A-α polarimetric...
The new advanced very high resolution (VHR) synthetic aperture radar (SAR) sensor is a kind of high-tech imaging radar developed rapidly in recent years, and it can get even less than 1 m high resolution SAR image. The feature of the VHR SAR image is different from the low or medium resolution SAR image and it contains more abundant information, so the traditional SAR image classification methods...
Graphics Processing Units (GPUs) are widely used to accelerate data-intensive applications. To improve the performance of data-intensive applications, higher GPU memory bandwidth is desirable. Traditional GDDR memories achieve higher bandwidth by increasing frequency, which leads to excessive power consumption. Recently, a new memory technology called high-bandwidth memory (HBM) based on 3D die-stacking...
In this paper the Supervised Locally Linear Embedding (SLLE) algorithm is introduced into polarimetric SAR (PolSAR) feature dimensionality reduction (DR) and land cover classification. SLLE technique, as a supervised nonlinear manifold learning method, can obtain a low-dimensional embedding space which preserves both the local geometric property of high-dimensional data and discriminative information...
Land cover change detection has long been a hot field in polarimetric synthetic aperture radar (SAR) applications. In certain cases, we care not only the changed areas but also from which type to another. This paper presents a supervised urban land cover change types identification method using a series of polarimetric descriptors from SAR observables and polarimetric decomposition. The normalized...
Distributed Denial of Service (DDoS) has already been one of the most serious threats to network security, and entropy-based approaches for DDoS attack detection are appealing since they provide more detailed insights than traditional traffic volume-based methods. In this paper, we propose a novel entropy-based DDoS attack detection approach by constructing entropy vectors of different features from...
Recently, machine learning is widely used in applications and cloud services. And as the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems. To give users better experience, high performance implementations of deep learning applications seem very important. As a common means to accelerate algorithms, FPGA has high performance, low power consumption,...
A compressed pornographic image recognition method is proposed by using incremental learning. For describing pornographic image, visual words are created from low-resolution (LR) image reconstructed from the compressed stream of the pornographic image. Covering algorithm is utilized to train and recognize the visual words in order to build the initial classification model of pornographic image. At...
In face recognition, LBP (Local Binary Patterns) is a very popular method, which can solve the defects of the traditional local feature extraction methods with fixed scale and small extraction scale. However, the LBP operator only describes the relationship between the center pixel and its neighborhood pixels, it ignores the relationship among the operators. 3DLBP (3 Dimensions Local Binary Patterns)...
This paper considers joint transceiver design and power control for K-user multiple-input multiple-output (MIMO) interference networks. Each source intends to communicate with its corresponding destination at a fixed data rate. Only local channel side information (i.e. knowledge related to the channels directly connected to a terminal) is available at each terminal. We propose iterative algorithms...
This paper presents a system to automatically generate car sample dataset for visual-based car detector training. The dataset contains multi-view car samples labeled with the car's pose, so that a view-discriminative training and car detection is also available. There are mainly two parts in the system: laser-based car detection and tracking generates motion trajectories of on-road cars, and then...
The self-organizing map (SOM) neural network has been used widely in multiple models approximation (MMA). However, the clustering property of SOM may not be fit for MMA. This paper introduces the idea of active learning into the training of SOM, especially for MMA. The neural network selects actively the training samples according to the approximation error of local models. As a result, the distribution...
In this paper, we investigate the bag-of-feature based medical image retrieval methods, which represent an image as a bag of local features, such as image patchs. To describe local feature bags effectively, most bag-of-feature methods learn a visual vocabulary containing a number of visual words via clustering. Different visual words have different importance in a medical image. The visual word weighting...
Automatically classifying the tissues types of region of interest (ROI) in medical imaging has been a important application in computer-aided diagnosis, such as classification of breast parenchymal tissue in the mammogram. Recently, bag-of-features method has show its power in this field, treating each medical image as a set of local features. In this paper, we investigate using the bag-of-features...
Facial feature tracking is a key step in facial dynamics modeling and affect analysis. Active Shape Model (ASM) has been a popular tool for detecting facial features. However, ASM has its limitations. Due to the finiteness of the training set, it cannot handle large variations in facial pose exhibited in video sequences. In addition, it requires accurate initiation. In order to address these limitations,...
In this paper, the concept of curriculum development is defined, how to implement the curriculum development in college education is described in eight aspects, the deficiencies in the process of curriculum development is analyzed and the methods are put forward. The class director's role in class management is necessary, the need of class director is described from five aspects in the college education,...
Target discrimination is the key step of automatic target detection in synthetic aperture radar (SAR) images. Aiming at the issue of aircraft discrimination in high resolution SAR images, a novel discrimination method is proposed with using texture features. First of all the method of gray level co-occurrence matrix is used to generate eight discrimination texture features: mean, variance, deficit...
In this paper, a novel Gabor-2DFisherface approach with selecting 2D Gabor principal components and discriminant vectors is proposed for face recognition. Gabor transform is an important frequency-domain analysis tool. The proposed approach combines it with discriminant analysis technique. This approach first preprocesses all image samples by using Gabor transform, and then calculates 2D Gabor principal...
The reasons of applying for teaching reform projects and the current situation are introduced in this paper, the teaching reform project pool management system is given and the operation methods with operation rules are analyzed which are helpful to improve the applied college teaching management quality.
Illumination variation is one of the critical factors affecting face recognition rate. A novel illumination compensation for face recognition is presented in this paper. First of all, a new illumination direction map is introduced, which is built using the block-based histogram equalization (Xudong Xie and Kin-Man Lam, 2005) and illumination model. Secondly, plane-fit method can be used to determine...
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