[PDF] Top 20 Video Concept Detection Using Convolutional Neural Network
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Video Concept Detection Using Convolutional Neural Network
... challenges. Video Concept detection is defined as a process of detecting concept present in the video or selected video ...frame. Video is the collection of multiple ...of ... See full document
8
Weeds Detection in Agricultural Fields using Convolutional Neural Network
... Every advantage has its disadvantage. This is several advantages that the robot consists of. The instability of the dc motor rotation causing it cannot stop at a certain time constant. Since position to stop is wrong ... See full document
5
Survey on Skin Disease Detection using Convolutional Neural Network
... Skin diseases are one of the most commonly seen infections among people. Due to the disfigurement and associated hardships, skin disorders cause lots of trouble to the sufferers. Speaking of skin cancer, the facts and ... See full document
8
Grapes Leaf Disease Detection using Convolutional Neural Network
... In [8] Authors have used 2 types of Flower dataset. Automated system is developed for the detection of the type of flower using CNN and Transfer Learning. Instead of building the model from scratch transfer ... See full document
5
Object Detection using Convolutional Neural Network in the Application of Supplementary Nutrition Value of Fruits
... image detection is unique most auspicious claims of visual object recognition, since it will help to estimate nutrition calories and improve commons ingestion ... See full document
5
Automatic diagnosis of imbalanced ophthalmic images using a cost-sensitive deep convolutional neural network
... lutional neural network (CS-ResCNN) classifier to diagnose ophthalmic diseases using retro-illumination ...Canny detection and Hough ...analyzed using a grid-search procedure to verify ... See full document
20
Spam detection in im images using convolutional neural networks
... These neural nets have to capacity to learn the hundreds of thousands of features, and almost intuitively make an intelligent guess of whether a given image is Spam or ... See full document
6
An analytical study of information extraction from unstructured and multidimensional big data
... event detection; ANN: artificial neural network; ASR: automatic speech recognition; AVS: automatic video summarization; BFM: Bayesian fusion model; CNN: convolutional neural ... See full document
38
Object Detection in Underwater Images using Faster Region based Convolutional Neural Network
... frame-disparities make optical flow methods to be had. Four If body-to-frame disparities are tremendous, a Kalmanfilter is most commonly used to perform temporal integration of extracted points. Nonetheless, incorrect ... See full document
5
A Detection algorithm based on Convolutional Neural Network
... logo detection, Wang Jian et al[7] proposed an image segmentation method ,which based on the geometric and positional features of the mark to determine the split identification ...station-based detection ... See full document
12
Integrated Animal Recognition and Detection Using Deep Convolutional Neural Network
... In this paper, we investigate the feasibility of infant recognition by their footprint using a 500 ppi commodity friction ridge sensor. We collected an infant footprint dataset in three sessions, consisting of 60 ... See full document
7
SCNN: A General Distribution Based Statistical Convolutional Neural Network with Application to Video Object Detection
... sequential network which only uses 3×3 stacked convolu- tional layers for feature ...its network-in-network structure which leads to effective extremely deep ... See full document
8
Plant Species Classification and Disease Detection using Convolutional Neural Network
... on detection and classification of leaf ...spices using image processing of plant ...noise using an isotropic di ...classification using classifier will be ... See full document
7
Prediction of Rice Diseases Using Convolutional Neural Network (in Rstudio)
... Abstract:- Detection of rice pest and diseases, and proper management and control of pest infested rice fields may result to a higher rice crop ...production. Using modern technologies, like smart phones, ... See full document
8
Identification Of Weeds From Crops Using Convolutional Neural Network
... artificial neural networks to do the process of pattern ...artificial neural networks imitates the functionality of the human brain and it contains millions neuron nodes connected to each other like a ... See full document
6
Human Face Recognition in Video using Convolutional Neural Network (CNN)
... dimensions using a saliency ...BRISK using a pyramid of ...the detection stages finally end, producing a set of keypoints with space and scale coordinates, what means that each one of them can be ... See full document
7
Detection of Diabetic Retinopathy using Convolutional Neural Network
... method using fundus images for DR have received a great deal of attention among ...hemorrhage detection method to help diagnose diabetic ...detected using density ...by using a 45-feature ... See full document
7
Facial Emotion Detection using Convolutional Neural Network
... Convolution Neural Networks has been an effective and common way to solve the problems like facial emotion ...Recurrent Neural Networks (RNN) because CNN will learn to recognize components of an ...also ... See full document
6
Video Summarization using Convolutional Neural Network
... large video databases. We introduce smart surveillance by using video summarization for various ...via Convolutional Neural Networks (CNN). Using this analysis, features are ... See full document
7
Improvements to Tracking Pedestrians in Video Streams Using a Pre-trained Convolutional Neural Network
... In order to improve the performance of the tracking results, a post stage processing step after all detection, and tracking steps is proposed. At this level, results consist of both completed tracks as well as ... See full document
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