[PDF] Top 20 Large-scale image-to-video face retrieval with convolutional neural network features
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Large-scale image-to-video face retrieval with convolutional neural network features
... Convolutional neural network features are becoming the norm in instance ...detection network, like Faster R-CNN, as a feature extractor for an image-to- video face ... See full document
6
Video Concept Detection Using Convolutional Neural Network
... proposed video concept detection using a deep CNN and GMM super vectors with the low level visual ...on large scale datasets due to their capability of joint feature and classifier ...unique ... See full document
8
A Survey on Video Classification Methods Based on Deep Learning
... Nowadays video classification method based on deep learning is still a hotspot in video understanding ...two-stream convolutional neural network and 3D convolutional ... See full document
7
Scalable Database Indexing and Fast Image Retrieval Based on Deep Learning and Hierarchically Nested Structure Applied to Remote Sensing and Plant Biology
... data retrieval model to manage, search, and retrieve unstructured and complex image ...efficient image retrieval system for real-time content-based searching through large-scale ... See full document
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Object Detection using Convolutional Neural Network in the Application of Supplementary Nutrition Value of Fruits
... and image process that contracts with spying instances of similar objects of a particular category (such as Food ,Animal, buildings, or cars) in digital pictures and ...represent face detection and ordinary ... See full document
5
A Review on Large-scale Video Classification with Recurrent Neural Network (RNN)
... content-based video indexing using Hidden Markov Models ...each image of the video ...based features liken average absolute deviation of the motion, centre of motion delta features are ... See full document
5
Convolutional Neural Networks and Hash Learning for Feature Extraction and of Fast Retrieval of Pulmonary Nodules
... medical image repositories is increasing ...these large databases leading to the need of content based medical image retrieval (CBMIR) ...convolution neural network (CNN) to ... See full document
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Human Face Recognition in Video using Convolutional Neural Network (CNN)
... the image and scale dimensions using a saliency ...through scale space is fundamental to achieve scale invariance and it is realized in BRISK using a pyramid of ...original image ... See full document
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Robust Face Recognition Based on Convolutional Neural Network
... 4.4M face image and firstly used it for face verification ...a large data set by semantic bootstrapping. The FaceNet [1] network, designed with the introduction of triplet loss in the ... See full document
6
Identification Of Weeds From Crops Using Convolutional Neural Network
... of network Architecture YannLeCun uses a new architecture which is good at object recognition in image dataset called the Convolutional Neural Network ...The convolutional ... See full document
6
Face Authentication Using Efficient Deep Convolutional Neural Network
... Convolutional Neural Network (CNN) has been widely used in variety of ...ImageNet Large Scale Visual Recognition Challenge (ILSVRC) ...for image recognition [8, 9, 10, 11], ... See full document
6
Data Hiding By Neural Network and Retrieval(Encrypted Image, Text, Audio and Video Files)
... the large allowance of facts and figures through the mesh will give mistakes while ...JPEG Image and Video ...JPEG image and video format to be moved using the cryptographic standards ... See full document
6
Recent Advancements in Machine Learning and Artificial Intelligence Techniques for Cancer Diagnosis
... the image processing technique and largely contributes in determining the outcome of the ...of image as background ...of image segmentation is clinical sample analysis for the diagnosis of the ... See full document
15
Combination of Multiple Acoustic Models with Multi-scale Features for Myanmar Speech Recognition
... As shown in Fig. 1, the combination module is a ROVER process on the N-best hypothesis lists from the decoding process of all models corresponding to different temporal scales. The decoding process for each model is ... See full document
10
Single Image Super-Resolution
... color image usually is an RGB image, which means it is composed of red, green and blue ...an image is split into its components, then we have three channels, one for each ...an image with size ... See full document
7
Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network
... the features of the images rather than the ...high-level features from the ResCNN and CS-ResCNN, and then employed the over-sampling and under-sampling technologies to balance the proportions of the ... See full document
20
Deep learning for smart agriculture: Concepts, tools, applications, and opportunities
... TensorFlow is an open source computing framework of Google that supports deep learning algorithms, including CNN, RNN, GAN and other variants, which can be used on Linux, Windows, and Mac platforms. TensorFlow has some ... See full document
13
MLVCNN: Multi-Loop-View Convolutional Neural Network for 3D Shape Retrieval
... Generally, 3D shapes have complex geometries and vari- ations, and thus it is very difficult to represent 3D shapes well, leading it a challenging task to retrieve 3D shapes ac- curately. There have been plenty of works ... See full document
8
Fruit Image Classification using Convolutional Neural Network
... In order to create our convolutional neural network we used Tensor Flow. This is an open source framework for machine learning created by Google for numerical computation using data flow graphs. ... See full document
13
Automatic Plastic Waste Segregation And Sorting Using Deep Learning Model
... to large-scale unlabeled ...Deep Convolutional Neural Network (DCNN) have being considered on indoor environment to classify categories of bottle objects ...Combined ... See full document
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