[PDF] Top 20 Performance evaluation of deep feature learning for RGB-D image/video classification
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Performance evaluation of deep feature learning for RGB-D image/video classification
... Figure 11: Some example images in the NYU Depth v1 dataset. It includes 6 object classes (bathroom, bedroom, bookstore, kitchen, living room and office). We can find 6 paired samples shown in this figure. In each pair, ... See full document
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Classification methods of a small sample target object in the sky based on the higher layer visualizing feature and transfer learning deep networks
... edge performance strength of the local eigen- vector can reflect the similarity between the local fea- ...local feature weight extracted from the target object images is obscure com- pared with the local ... See full document
12
Study on Machine Learning and Deep Learning Methods for Human Action Recognition
... in deep networks captures the temporal information from the consecutive ...a video. Convolutional Neural Network (CNN) is the simple deep networks which are used in action ...from image to ... See full document
13
A Deep Learning Model for Image Classification
... machine learning algorithms uses these extracted features to classify the ...machine learning algorithms have been applied to multilabel image classification problems which have also brought ... See full document
5
Improving ultrasound video classification: an evaluation of novel deep learning methods in echocardiography
... input image of 224 by 224 pixels for a 10 frame ...a video to be ...of feature maps which results in significantly fewer trainable parameters and we found led to much faster convergence with improved ... See full document
11
A Survey of Fine Grained Image Classification Based on Deep Learning
... The deep learning technology has shown impressive performance in various vision tasks such as image classification and object ...of deep learning techniques bring ... See full document
8
A Novel Method for Remotely Sensed Hyperspectral Image Classification Based on Convolutional Neural Network
... Hyperspectral image classification is the process of assigning land cover classes to ...landscape, image processing and classification approaches affect the success of ...in image ... See full document
10
AN IOT BASED FRAMEWORK FOR STUDENTS INTERACTION AND PLAGIARISM DETECTION IN PROGRAMMING ASSIGNMENTS
... images, video, and audio) poses challenges in developing Multimedia Information Retrieval Systems ...including video and audio media as query input that can increase the amount and variety of information in ... See full document
17
Semantic Adversarial Network with Multi-Scale Pyramid Attention for Video Classification
... the performance is still worse than two-steam CNN based ...in video, which leads to limited generalization ...fact, RGB frames contain abundant of semantic information, which can greatly improve ... See full document
8
A Survey on Video Classification Methods Based on Deep Learning
... dynamic feature extraction in the two-stream network structure was first proposed by Gibson in ...the image sequence, so as to calculate the motion information of objects in video between adjacent ... See full document
7
Comparative Evaluation of Deep Architectures for Face Recognition in Unconstrained Environment (FRUE)
... as Deep hidden IDentity (DeepID), consists of network fusion of ...2 D transformations. Then the input image is segmented into 60 patches to extract different features from different parts of face ... See full document
8
Performance Evaluation of Several Machine Learning Techniques Used in the Diagnosis of Mammograms
... Fig. 1 shows general breast image classification steps. First input mammograms from a specific database and apply different pre-processing techniques, after that applied different statistical ... See full document
5
Hyperspectral image classification via contextual deep learning
... Pixel-wise classification methods process each pixel independently without considering the spatial informa- tion, but spatial contextual information of HSI is as impor- tant as the spectral information ...of ... See full document
12
ACM: Adaptive Cross-Modal Graph Convolutional Neural Networks for RGB-D Scene Recognition
... RGB image classification has achieved significant perfor- mance improvement with the resurge of deep convolutional neural ...mono-modal deep models for RGB image still ... See full document
9
A deep-learning based feature hybrid framework for spatiotemporal saliency detection inside videos
... Saliency detection models in general can be categorized into visual attention prediction and saliency object detection. In this paper, we propose a deep learning framework for predicting eye fixation ... See full document
20
A Review on Large-scale Video Classification with Recurrent Neural Network (RNN)
... understanding image content. It gives state of the art which results on image recognition, segmentation, detection and ...for video classification are discussed here and compare all the ... See full document
5
Unsupervised Deep Video Hashing with Balanced Rotation
... Next, the retrieval results are evaluated by using various hashing strategies adopted in the phase of code learning in or- der to validate the claimed contributions. Three combinations are included: CCA+ITQ, ... See full document
7
Deep Learning-Based Classification of Remote Sensing Image
... machine learning algorithm, which means a variety of forms of remote sensing images belong to hundreds different kinds objects which had been manually labeled into accurate ... See full document
5
Characterization of the spectral distribution of hyperspectral imagery for improved exploitation
... The feature maps in Figure 3.12 shows that the PDD for this particular image, from the HyMap sensor of Cooke City, MT, does not strongly correspond to the three regions of interest shown in the original ... See full document
220
Domain-Adversarial Training of Neural Networks
... three learning algorithms (DANN, NN, and SVM) on these ...a learning rate µ of 10 −4 for both DANN and the ...better performance than the NN and the SVM, with probabilities ... See full document
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