[PDF] Top 20 Fast ROI Detection for Speed up in a CNN based Object Detection
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Fast ROI Detection for Speed up in a CNN based Object Detection
... Most of lights including LED flickers with high frequency. The flicker cannot be perceived by a human, but it has an effect on a captured image. Figs.1 (a) and (b) show images with the LED flicker noise, which are ... See full document
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Implementation of Regional-CNN and SSD Machine Learning Object Detection Architectures for the Real Time Analysis of Blood Borne Pathogens in Dark Field Microscopy
... the CNN computed features and the Region Proposal Network half of the model by using the features collected to detect bounding boxes that have a probability of containing the object(s) of interest by ... See full document
10
Machine Learning Tool Development in Fire Safety Design Review
... of object detection technique to recognize and localize the less-featured building elements on the architectural drawings was ...An object detection engine using Faster R-CNN deep ... See full document
5
Real-Time Facial Emotion Recognition Using Fast R-CNN
... set. Fast Region-based Convolutional Neural Network, an object detection algorithm; used to detect facially expressed emotion in real-time by classifying proposed ...The Fast ... See full document
74
Object Detection in X-ray Images Using Transfer Learning with Data Augmentation
... the detection of these objects are Sliding Window based CNN (SW-CNN) [6], Faster R-CNN, Region-based Fully Convolutional Networks (R-FCN) and, You Only Look Once (YOLO) V2 ... See full document
7
Weakly Supervised Object Detection by using Fast R CNN
... sign detection system generates input boxes by region ...a RoI pooling layer that is then wont to classify the image inside the planned region and predict the offset values for the bounding ... See full document
6
REAL TIME MOVING OBJECT DETECTION USING C-MODEL WITH CNN
... moving object based on vision has also developed ...moving object detection, including the difference method (background difference method and time difference method) and optical flow method ... See full document
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Object detection algorithm for unmanned surface vehicle using faster R-CNN
... real-time detection. When CNN is trained with high quality and quantity of dataset, it detected the model ship with a probability of almost 70% and the average distance error was within 3 ... See full document
12
Design And Develop Object Detection System For Blind People Based On CNN Image Recognition
... in object detection is ...proposal based on the edge map of the ...faster speed over selective search in ...intelligent object detection system for blind people based on ... See full document
24
Traffic flow estimation with data from a video surveillance camera
... the object detectors are based on the convolutional neural networks (CNN) and can be roughly divided into two classes: single-stage detectors and two-stage ...generally fast and predict ... See full document
15
Multiple Object Detection and Tracking: A Survey
... Multiple Object Tracking is the process of locating multiple objects over time in a video ...stream. Object detection and classification are two prior steps before performing tracking over video ... See full document
7
OBJECT TRACKING BASED ON MOVING OBJECT DETECTION
... The background subtraction method is the common method of motion detection. It is a technology that uses the difference of the current image and the background image to detect the motion region, and it is ... See full document
9
Ciprofloxacin Nano-Composite Carbon Paste and PVC Membrane Potentiometric Sensors
... potentiometric detection based on ion– selective electrodes (ISEs) offers the advantages of speed and ease of preparation and procedures, relatively fast response, reasonable selectivity ... See full document
13
Smart Camera for Object Detection, Distance and Relative Speed Estimation
... make speed calculation ...the object, a rectangle of random colour is drawn with name of object, accuracy of detection, distance and relative speed as ... See full document
5
Senet Cnn Based Tomato Leaf Disease Detection
... and CNN layer concept for better classification. CNN is performed by using the number of layer and kernel ...the detection of disease in tomato leaf with use of minimal computing ... See full document
5
Neural Network Based ROI Detection and Hybrid Image Compression
... Interest based compression is an efficient method of compression for images with a particular part to be most ...the ROI with lossless compression while the rest of image with lossy compression ...than ... See full document
5
Cetrimide Potentiometric PVC membrane Sensor
... Plasticizer acts as a membrane solvent allowing homogeneous dissolution and diffusional mobility of the ion-pair inside the membrane [27-34]. The plasticizer should be water- immiscible liquid of low vapor-pressure, ... See full document
10
Artificial Intelligence and Convolutional Neural Network for Recognition of Human Interaction by Video from Drone
... utilized CNN, it improves the technique with ...pre-trained CNN with eliminating the classification layer and utilization of the output of the last layer as an image descriptor generate a probability vector ... See full document
20
A Fast Moving Object Detection Technique In Video Surveillance System
... moving object by doing difference of consecutive frames (two or three) in a video ...the object the frame differencing algorithm fail in extracting all pixels of the Paresh ... See full document
6
Detection of Scratches on Cars by Means of CNN and R-CNN
... When making the classification of the sections in their respective category, there were a few error cases, representing only 3.11%. For the most part, the error cases were due to the reflection that some cars had in the ... See full document
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