high level image classification
Region-based convolutional neural network using group sparse regularization for image sentiment classification
... sentiment classification methods have shown superior performance of sentiment prediction against traditional label sentiment classification methods for images [6, ...Rarely, image sentiment ...
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An Efficient Image Classification Using Class Imbalance In High-Dimensional Data
... Object recognition has been an active research focus in field of image processing. Using object models that are known a priori, an object recognition system finds objects in the real world from an image. ...
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Large Scale Image Classification using High Performance Clustering
... 2) MapReduce and Hadoop: On the other hand, Hadoop is data-centric. HDFS [25] is used to store and manage big data so that users are freed from the data accessing and loading steps required in MPI. In addition, ...
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Interaction between High Level and Low Level Image Analysis for Semantic Video Object Extraction
... their extraction is a di ffi cult and sometimes loose task. For the specific implementation used in this paper, mo- tion is used as a clue to semantic information. In this frame- work, an automatic algorithm is presented ...
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Skin Lesion Segmentation and Classification Based on High Level Features
... The input is skin lesion image. Initialize the path and browsing the image. Concencate the string. Create the ellipse and crop the image, so getting ROI image. ROI stands for region of ...
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Transfer Learning for High Resolution Aerial Image Classification
... “airplane” image from the dataset is fed into the modified pre-trained AlexNet model, the fine-tuned AlexNet model using the traditional fine-tune method, and the fine-tuned AlexNet model with the proposed ...the ...
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Image Segmentation in Satellite Image using Optimal Texture Measures
... in high resolution satellite images requires substantial amendment in the conventional segmentation ...satellite image is segmented using optimal texture measures. Satellite image used in this paper ...
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Advances in Scene Classification of Remotely Sensed High Resolution Images and the Existing Datasets
... Scene classification of remotely sensed images has shown a significant improvement in the recent years as it is used in various applications such as urban planning, urban mapping, management of natural resources, ...
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Low-level and high-level modulations of fixational saccades and high frequency oscillatory brain activity in a visual object classification task
... the level of the superior colliculus subcortical low-level inputs converge with cortical loops that provide high- level information used for ocular ...the high- est rates of ...
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Vehicle Image Classification using Image Fusion at Pixel Level based on Edge Image
... synthesize image or image array information about a different scene and produce new explanation about that ...edge image and reflect better outline of the ...The classification is done based ...
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Classification for Liver Diseases Based on Ultrasound Image Texture Features
... (LRE), High Gray-Level Run Emphasis (HGRE), Low Gray- Level Run Emphasis (LGRE), pair-wise combinations of the length and gray level emphasis (SRLGE, SRHGE, LRLGE, LRHGE), Run-Length ...
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Mining Mid-level Features for Image Classification
... really high numbers within this small set of ...of image classification are restricted to standard class-based association rules [2], standard discriminative pattern mining approaches [20, 25, 34, ...
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Large Scale Image Classification using High Performance Clustering
... Though the above methods are not perfect, they all reduce broadcast time to a great extent. Still, none of them are applied in data-centric solutions, where instead a simple algorithm is commonly used. Hadoop relies on ...
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Detection of the urban expansion over agricultural land using LULC change detection techniques:case study El-Mahalla el-koubra City-Egypt
... direct classification, image differencing, image rationing, image symmetric relative difference, change vector analysis (CVA), and principal component differencing ...
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Data Classification Particle Swarm Optimization and Gravitational Search Algorithm
... Abstract: Classification is an important problem in data ...learning, classification has been studied extensively by the AI community as a possible solution to the “knowledge acquisition” or “knowledge ...
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Recent Advancements in Machine Learning and Artificial Intelligence Techniques for Cancer Diagnosis
... digital image processing for medical ...digital image processing and machine learning, various methods were listed which were used for processing the images based on the type of images acquired, ...
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Learning hierarchically organized science categories: simultaneous instruction at the high and subtype levels
... the high-level names, whereas the second group studied the pictures with both the high-level and subtype ...their high-level categories. Participants in the ...
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SEMI-SUPERVISED HIGH-RESOLUTION IMAGE CLASSIFICATION USING CRF MODEL
... spectral-spatial classification many researchers have complete deal of ...object-oriented classification method the another obvious way to regard the spatial ...the image into homogeneous objects and ...
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A baseline for multi-label image classification using an ensemble of deep convolutional neural networks
... multi-label image classification have fo- cused on designing more complex architectures of deep neu- ral networks such as the use of attention mechanisms and re- gion proposal ...multi-label image ...
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HSV-PCA AND IHS-PCA BASED IMAGE FUSION TECHNIQUES
... fused image, without introducing artifacts or inconsistencies, which may damage the quality of the fused image and distract or mislead the human ...fused image irrelevant features and noise should be ...
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