[PDF] Top 20 Neural Networks Approach in Detection of Object using Radar System
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Neural Networks Approach in Detection of Object using Radar System
... systems approach and stable adaptive laws which gives the assurity the global stability of the overall system are derived based on properties of those ...years, Neural Network based control ... See full document
6
A REVIEW ON UNAUTHORISED OBJECT DETECTION USING IR RADAR
... this system detection and recognitions of ground as well as air objects is done using IR ...on detection and recognition of unauthorized objects ...identification, detection, and ... See full document
7
Image Segmentation and Edge Detection Using a Neural Networks RBF Approach
... The system consist of a multilayer perceptron (MLP)-like network that performs image segmentation by RBF technique of the input image using labels automatically pre-selected by a fuzzy clustering ... See full document
6
Deep Learning Techniques for Object Detection
... one-stage networks in order to maintain accuracy while eliminating ...Real-time System research in Computer Vision focuses on Video Object Detection pertaining to motion-blur and de-focus, ... See full document
8
Fault Detection and Isolation of Vehicle Driveline System
... computing approach to design fault detection and isolation (FDI) systems for Vehicle ...Neuro-fuzzy networks have been used in the diagnosis of defects because of its specific advantages and ... See full document
11
Improved Intrusion Detection System with Optimization Enabled Deep Neural Networks
... intrusion detection mechanism in the networks, which is performed using the optimization-based deep belief neural networks ...classified using the DBN classifier and the ... See full document
6
Spatially Invariant Unsupervised Object Detection with Convolutional Neural Networks
... initial object detec- tion step wherein the pixel-level information is transduced into high-level object ...either using ad hoc, task/environment specific object detec- tion methods (Garnelo, ... See full document
9
3D Object Recognition by Classification Using Neural Networks
... an approach based on neural networks which is a first step to split the objects into n samples and then calculate the errors for these ...samples. Using the proposed method, they will be ... See full document
5
A Novel Intrusion Detection System Using Neural-Fuzzy Classifier for Network Security
... an approach in [2] to detect an attack, which uses artificial neural networks and Back propagation ...proposed approach is applied to the KDD CUP'98 data ...used system behavior as ... See full document
6
Captioning for Motion Detection for video surveillance Applications using Deep Learning
... tested using the MS COCO ...top-down approach, bottom-up approach with sematic ...calculated using the top down and bottom up mechanisms at object ...up approach uses a faster ... See full document
6
Specific RCS for Describing the Scattering Characteristic of Complex Shape Objects
... Analytical calculation methods cannot be used for RCS calculation of the complex shape objects, so in this case some numerical approaches should be treated [5]. For example, one can apply facet method [6, 7] or the ... See full document
10
A FUZZY APPROACH FOR REPRESENTATIVE NODE SELECTION IN CROSS LAYER TCP
... behavior system can provide us with a powerful strategies that can be applied to IDS ...social system of honeybees on organizing and protecting their colony is one of the feasible strategies that can be ... See full document
10
Recognizing Handwritten Alphabets using Neural Networks
... The human brain is one of the most fascinating objects in the world. It is rightfully the epitome of what modern day computers strive for. Since the advent of technology, humans have been obsessed with making systems ... See full document
5
Automation of Assessment and Approximation of Software Reliability
... of Neural Network for Predicting Software Development Faults using Object- Oriented Design Metrics, ...on Neural Information Processing (ICONIP‟02), November ... See full document
45
Prediction of Stock Prices Using Artificial N...
... artificial neural network is a “computing architecture comprising of simple processing elements, neurons, that work in parallel and connect with each other by sending signals (Krawiec and Stefano ski, 2003: 83) 7 ... See full document
6
Energy Efficient Neural Network Technique to Recover Collision in WSN
... Sensor Networks (WSN) are highly distributed self-organized ...sensor networks are equipped with only Omni-directional antennas, which can cause high ...wireless networks. In this paper we are ... See full document
8
A Novel Compressed Deep Stacking Neural Network Based Classifier for the Monitoring and Classification of Multiple Power Quality Disturbances
... Detection and classification of single and combined power quality disturbances using neural 566. networks[r] ... See full document
26
Neural networks for object recognition
... feedforward networks that use a form of supervised learning called back-propagation ...a neural network, so a brief description must ...network using a gradient descent learning rule so that next ... See full document
42
UAV for Surveillance and Mapping at Construction Sites
... Crowd Detection for Drone Flight Safety Using Convolutional Neural Networks” propose a system that can be used to distinguish the crowded and non crowded area with the help of ... See full document
7
Steganography Detection using Functional Link Artificial Neural Networks
... coded using OutGuess, no change can be observed between the uncoded and coded image to the naked ...image. Using this concept, we feed the neural network with the Huffman code of the uncoded images ... See full document
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