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Learning a kernel function for classification with small training samples

Tomer Hertz, Aharon Bar Hillel, Daphna Weinshall
2006 Proceedings of the 23rd international conference on Machine learning - ICML '06  
We demonstrate performance enhancement on two challenging tasks: digit classification with kernel SVM, and facial image retrieval based on image similarity as measured by the learnt kernel.  ...  This kernel is also shown to enhance retrieval based on data similarity.  ...  These kernels can then be used for classification with kernel SVM. They can also be used directly for retrieval based on similarity (as measured by the kernel).  ... 
doi:10.1145/1143844.1143895 dblp:conf/icml/HertzBW06 fatcat:mgbo7fkgsva4pegbbyij3jiina

Dimensionality Reduction of Features using Multi Resolution Representation of Decomposed Images
english

Avi Bleiweiss
2014 Proceedings of the 3rd International Conference on Pattern Recognition Applications and Methods  
Dimensionality Reduction of Features using Multi Resolution Representation of Decomposed Images.  ...  We conduct experiments on both non and correlated image sets, expressed in raw feature vectors of one million elements each, and demonstrate robust accuracy in applying our features to a linear SVM classifier  ...  of normalizing the cell based feature map, C, with respect to each factor, followed by truncation.  ... 
doi:10.5220/0004917403160324 dblp:conf/icpram/Bleiweiss14 fatcat:syqungk2czbmxm4sttavsn2rim

A Review on Deep Learning Approaches for 3D Data Representations in Retrieval and Classifications

Abubakar Sulaiman Gezawa, Yan Zhang, Qicong Wang, Lei Yunqi
2020 IEEE Access  
According to the findings in this work, multi views methods surpass voxel-based methods and with increased layers and enough data augmentation the performance can still be increased.  ...  Due to growing interest in 3D object retrieval and classification tasks, the performance of different 3D object retrieval and classification on ModelNet40 dataset were compared.  ...  In this method, a multi-modal voxel-Net (MVX-Net) is presented which augment LIDAR points with semantic image features and learn to fuse image and LiDar features at early stages.  ... 
doi:10.1109/access.2020.2982196 fatcat:jnya5rscynf3zm7efuucqxafri

ChiTransformer:Towards Reliable Stereo from Cues [article]

Qing Su, Shihao Ji
2022 arXiv   pre-print
(GPCA) layers is designed to enable feature-sensitive pattern retrieval between views while retaining the extensive context information aggregated through self-attentions.  ...  Monocular cues from a single view are thereafter conditionally rectified by a blending layer with the retrieved pattern pairs.  ...  While the prevalent MHA seeks for multi-level context instead of retrieval since tokens are mapped to different (sub-)spaces for each head that generates its own attention weights and output with the projected  ... 
arXiv:2203.04554v3 fatcat:6mbovuhexrc6jhwre3vzcy7fxy

Leaf Image-based Plant Disease Identification using Color and Texture Features [article]

Nisar Ahmed, Hafiz Muhammad Shahzad Asif, Gulshan Saleem
2021 arXiv   pre-print
In this study, six color features and twenty-two texture features have been calculated. Support vector machines is used to perform one-vs-one classification of plant disease.  ...  on the Gray-Level Co-occurrence Matrix (GLCM), feature selection and classification.  ...  TABLE 2 :Table 3 . 23 FEATURE SELECTED THROUGH FORWARD FEATURE SELECTION WITH MULTI-SVM AS CRITERION ReliefF algorithm is a feature ranking algorithm and this ranking can be truncated based on weights  ... 
arXiv:2102.04515v1 fatcat:rw4m42l22zcavjpavks3z5guvi

Fault Detection and Classification of Aerospace Sensors using a VGG16-based Deep Neural Network [article]

Zhongzhi Li and Yunmei Zhao and Jinyi Ma and Jianliang Ai and Yiqun Dong
2022 arXiv   pre-print
To truncate and compress the FDC net size (hence its running time), we perform model pruning on the fine-tuned net.  ...  Compared with traditional model-based fault detection and classification (FDC) methods, deep neural networks (DNN) prove to be effective for the aerospace sensors FDC problems.  ...  Hang Zhao for the discussions on this paper.  ... 
arXiv:2207.13267v1 fatcat:c4akf6xq6vesjbmkkx5mnr267y

Pedestrian Attribute Recognition with Graph Convolutional Network in Surveillance Scenarios

Xiangpeng Song, Hongbin Yang, Congcong Zhou
2019 Future Internet  
In this paper, we treat pedestrian attribute recognition as multi-label classification and propose a novel model based on the graph convolutional network (GCN).  ...  The model is mainly divided into two parts, we first use convolutional neural network (CNN) to extract pedestrian feature, which is a normal operation processing image in deep learning, then we transfer  ...  Our model use ResNet-101 to extract pedestrian image features. We randomly cropped each training image and resized into 224 × 224 resolution with horizontal flips for data augmentation.  ... 
doi:10.3390/fi11110245 fatcat:ws2pxlz6tjdmhn7iis4bfxcowi

Building segmentation through a gated graph convolutional neural network with deep structured feature embedding

Yilei Shi, Qingyu Li, Xiao Xiang Zhu
2020 ISPRS journal of photogrammetry and remote sensing (Print)  
Yet one central issue remains: the precise delineation of boundaries.  ...  Our proposed framework with the new GCN architecture outperforms state-of-the-art approaches.  ...  The authors thank the Gauss Centre for Supercomputing (GCS) e.V. for funding this project by providing computing time on the GCS Supercomputer SuperMUC at the Leibniz Supercomputing Centre (LRZ) and on  ... 
doi:10.1016/j.isprsjprs.2019.11.004 pmid:31929682 pmcid:PMC6946440 fatcat:kj4dshhgujdnbilmkbnzifu7ci

RVMDE: Radar Validated Monocular Depth Estimation for Robotics [article]

Muhamamd Ishfaq Hussain, Muhammad Aasim Rafique, Moongu Jeon
2022 arXiv   pre-print
A variant of feature pyramid network (FPN) extensively operates on fine-grained image features at multiple scales with a fewer number of parameters.  ...  FPN feature maps are fused with sparse radar features extracted with a Convolutional neural network. The concatenated hierarchical features are used to predict the depth with ordinal regression.  ...  RVMDE), RESULTS BASED ON MULTIPLE CHANNEL BASED ENHANCED RADAR (MER), IMAGE.  ... 
arXiv:2109.05265v3 fatcat:p6v4sdrmtveo5i5cykzcbtq2ay

A survey on Deep Learning Advances on Different 3D Data Representations [article]

Eman Ahmed, Alexandre Saint, Abd El Rahman Shabayek, Kseniya Cherenkova, Rig Das, Gleb Gusev, Djamila Aouada, Bjorn Ottersten
2019 arXiv   pre-print
Recently, with the availability of both large 3D datasets and computational power, it is today possible to consider applying deep learning to learn specific tasks on 3D data such as segmentation, recognition  ...  We also discuss how Deep Learning methods are applied on each representation, analyzing the challenges to overcome.  ...  The proposed MVD-ELM was employed on 20 multi-view depth images that were uniformly captured with a sphere at the centre of the 3D object.  ... 
arXiv:1808.01462v2 fatcat:iuoay2sddjdqjbgm2nai6pa7gq

Bootstrap sequential projection multi kernel Locality Sensitive Hashing

Harsham Mehta, Deepak Garg
2014 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI)  
For this two algorithms are proposed one is weighted multi kernel LSH that calculated weight of each kernel and dedicated the hashing bits accordingly and the other one is boosting multi kernel LSH that  ...  Experimental Procedure We firstly started with analyzing of single kernel based LSH and based on that we derived kernel matrix of random data set based on each feature set.  ... 
doi:10.1109/icacci.2014.6968294 dblp:conf/icacci/MehtaG14 fatcat:hjnzm5fayfesjmaaau33w2bikq

CSPNet: A New Backbone that can Enhance Learning Capability of CNN [article]

Chien-Yao Wang, Hong-Yuan Mark Liao, I-Hau Yeh, Yueh-Hua Wu, Ping-Yang Chen, Jun-Wei Hsieh
2019 arXiv   pre-print
The proposed networks respect the variability of the gradients by integrating feature maps from the beginning and the end of a network stage, which, in our experiments, reduces computations by 20% with  ...  The CSPNet is easy to implement and general enough to cope with architectures based on ResNet, ResNeXt, and DenseNet. Source code is at https://github.com/WongKinYiu/CrossStagePartialNetworks.  ...  CSPNet separates feature map of the base layer into two part, one part will go through a dense block and a transition layer; the other one part is then combined with transmitted feature map to the next  ... 
arXiv:1911.11929v1 fatcat:nujkocv6drhpddf4qkdf7vvi4q

Classifying functional nuclear images with convolutional neural networks: a survey

Qiang Lin, Zhengxing Man, Yongchun Cao, Tao Deng, Chengcheng Han, Chuangui Cao, Linjun Zhang, Sitao Zeng, Ruiting Gao, Weilan Wang, Jinshui Ji, Xiaodi Huang
2020 IET Image Processing  
Finally, they discuss research challenges and directions for developing technological solutions to classify nuclear medicine images based on the CNN technique.  ...  According to the diseases of concern, they then classify the existing CNN-based work on the classification of functional nuclear images into three different categories.  ...  Classification: At this stage, the extracted features (feature maps) are inputs for the dimension of the weight matrix of the final neural network.  ... 
doi:10.1049/iet-ipr.2019.1690 fatcat:i4h7n4hsc5b2lenwmzekybxwte

2021 Index IEEE Transactions on Signal Processing Vol. 69

2021 IEEE Transactions on Signal Processing  
., +, TSP 2021 5846-5858 Adaptive Filters With Robust Augmented Space Linear Model: A Weight-edk-NN Method.  ...  ., +, TSP 2021 1995-2009 Feature selection On the Adversarial Robustness of LASSO Based Feature Selection.  ...  On Unlimited Sampling and Reconstruction. 3827-3839 Integer programming Generalized Non-Redundant Sparse Array Designs.  ... 
doi:10.1109/tsp.2022.3162899 fatcat:kcubj566gzb4zkj7xb5r5we3ri

2021 Index IEEE Signal Processing Letters Vol. 28

2021 IEEE Signal Processing Letters  
Upadhyay, U., +, LSP 2021 523-527 Multi-Function Radar Signal Sorting Based on Complex Network. Chi, K., +, LSP 2021 91-95 Multi-View Clustering Based on Invisible Weights.  ...  Qi, L., +, LSP 2021 1011-1015 Content-based retrieval Dark-Aware Network For Fine-Grained Sketch-Based Image Retrieval.  ... 
doi:10.1109/lsp.2022.3145253 fatcat:a3xqvok75vgepcckwnhh2mty74
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