Object Classification
k-NN Boosting Prototype Learning for Object Classification
... In this section we present experimental results of MLNN vs plain 𝑘-NN on a database of real objects. We carried out ex- periments in order to investigate the improvements brought by boosting on nearest neighbor voting. ...
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Object Classification in Still Images
... the Object Classification is to classify the objects in ...images. Classification aims for the recognition of generic classes, which is also known as Generic Object ...Specific Object ...
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Geometric Unified Method in 3D Object Classification
... 3D object classification task is easy to interpret right from its name, even without any math or computer science ...3D object classification simply means that given a certain object, ...
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Non-parametric context-based object classification in images
... in classification accura- cy when context was added to it ...context-based object classification, but that it is also in direct dependence on the success of the basic appearance-based ...the ...
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An Intelligent System for Object Classification in Video Surveillance
... object classification, in to their respective categories some pre- processing is done which include object detection and shadow ...the classification result more ...this classification ...
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Shape based Object Classification using Knowledge Vector Code
... ABSTRACT: As more information is digitized more and more digital images have been generated around the world. Efficient way of description and classification of objects is a well needed application to identify the ...
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Object Classification Using Stacked Autoencoder and Convolutional Neural Network
... The training and the testing datasets first need to undergo feature engineering - a process that transforms input patterns into low-dimensional vector representations [2]. In the training dataset, class labels of known ...
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Object Classification and Detection in High Dimensional Feature Space
... is that the Fourier transform is linear, enabling one to do the addition of the convolutions across the K feature planes in the frequency domain, and be left in the end with only one inverse Fourier transform to do, ...
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Time course of information processing in visual and haptic object classification
... Rapid representational processes may have been better reflected by gamma-band activity, which has been extensively studied in object representation (for recent reviews see Tallon-Baudry, 2009; Martinovic and Busch, ...
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GPU acceleration of object classification algorithms using NVIDIA CUDA
... This method follows the same concept as the previous one: perform the final classification in parallel. Rather than performing an iterative search for the maximum value, a reduction could be used to find the ...
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A LITERATURE SURVEY ON OBJECT CLASSIFICATION TECHNIQUES
... Image classification is a standout amongst the most complex ranges in image ...the classification strategies there are two sorts of Classification strategies, specifically Supervised ...
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Pose Normalization Network for Object Classification
... The results clearly depicts the robustness of the PNN in out-of-plane rotated object classification as compared to the CNN baseline. Similar training dataset are used, however the training methodology enables the ...
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On Shape Description and Optimization for Object Classification
... Recall that a skeleton consists of several collinear points. The famous projective invariant of collinear points is the so-called cross-ratio. A cross-ratio is a function of four collinear points defined in terms of ...
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Applications of Hyperspectral Remote Sensing in Ground Object Identification and Classification
... Due to the complexity and similarity of urban features, hyperspectral data could best reflect its high spectral resolution characteristics in this field, and could dis- tinguish urban features with similar spectral ...
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Video Object Tracking, Classification and Segmentation in Complex Wavelet Domain
... Recent advances in digital imaging technology, computational speed, storage capacity, continuous increase in computational capabilities of hardware at low cost, and networking have made it possible to capture, ...
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Moving object detection and classification using neuro-fuzzy approach
... object’s classification task in surveillance system ...the classification of vehicle frontal-view images use a combination of low level local features and high level global features through two stages of ...
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Cloud-based scalable object detection and classification in video streams
... This section explains the results obtained by executing the experiments with the dataset and the experimental setup with two di↵erent configurations mentioned in Section 6. This section is further divided into three ...
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Recognition and Classification of Object Images Using Features Extraction
... and classification of fruits, pests, objects, vehicle parking system and many more machine vision ...tell object identity and category with the simple glance, based on its appearance, on opposite to it ...
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Analysing various methods for object extraction and the classification of kitchens
... In the last few years there have been great successes in the application of deep and machine learning for the use of both object detection and classification. However, when there is a limited amount of data ...
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Object Detection, Extraction and Classification using Image Processing Technique
... Object detection means determine how many objects are present in an image. So for this after segmented the input image find the morphological structure of the input image, and then open the morphological image in ...
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