Search Results - (( learning classification using algorithm ) OR ( frames detection using algorithm ))
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1
Deep learning object detector using a combination of Convolutional Neural Network (CNN) architecture (MiniVGGNet) and classic object detection algorithm
Published 2020“…This paper presented an analysis performance of deep learning object detector by combining a deep learning Convolutional Neural Network (CNN) for object classification and applies classic object detection algorithms to devise our own deep learning object detector. …”
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
Published 2023“…The Viola-Jones algorithm is then used for face detection on the processed grayscale images. …”
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3
Vibration Signal for Bearing Fault Detection using Random Forest
Published 2024“…The primary objective of this research is to evaluate the bearing defect detection accuracy of the RF classifier. First, run four loops that cycle over each feature of the data frame corresponding to the daytime index to determine the bearing states. …”
Conference Paper -
4
Plant disease detection using deep learning
Published 2024“…The success of deep learning (DL) has greatly promoted the use of computer vision technology in smart agriculture. …”
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Final Year Project / Dissertation / Thesis -
5
CNN architectures for road surface wetness classification from acoustic signals
“…Wetness on the road surface has an impact on road safety and is one of the leading causes of weather-related accidents. Although machine learning algorithms such as recurrent neural networks (RNN), support vector machines (SVM), artificial neural networks (ANN) and convolutional neural networks (CNN) have been studied for road surface wetness classification, the improvement of classification performances are still widely being investigated whilst keeping network and computational complexity low. …”
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Automated underwater vision system for detection and classification of marine life using CNN YOLO-based model / Mohamed Syazwan Asyraf Rosli
Published 2022“…Recently, the integration of computer vision and machine learning has given solutions to improve the underwater detection system by using intelligent classifier algorithm in real-time computer vision to detect underwater animals with challenging environments. …”
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Thesis -
7
HUMAN MOTION ANALYSIS IN VIDEO SURVEILLANCE SYSTEM
Published 2019“…A video sequence consists of sequences of frame, with the detection algorithm, these frames can be analyzed and detect any” “abnormal behavior such as crime.” …”
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Final Year Project -
8
An FPGA based embedded vision system for real-time motion detection
Published 2015“…The system was able to process 10 pixels at one clock cycle to detect object by using only 643 logic blocks.…”
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Proceeding Paper -
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An Algorithm for Vehicle Detection and Tracking
Published 2010“…In this paper, we propose a vehicle detection and tracking algorithm. The detection is done using the median filtering and blob extraction. …”
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Conference or Workshop Item -
10
Case Slicing Technique for Feature Selection
Published 2004“…One of the problems addressed by machine learning is data classification. Finding a good classification algorithm is an important component of many data mining projects. …”
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Thesis -
11
Depth frame loss concealment for wireless transmission utilising motion detection information
Published 2014“…The methods are able to facilitate a frame copy algorithm and a high correlation of colour and depth frames to conceal depth frame loss. …”
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Thesis -
12
Moving objects detection from UAV captured videos using trajectories of matched regional adjacency graphs
Published 2017“…In the past, MOD was mainly tackled using image registration, which discovers correspondences between consecutive frames using pair-wise grayscale spatial visual appearance matching under rigid and affine transformations. …”
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13
Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
14
An Improved Action Key Frames Extraction Algorithm for Complex Colour Video Shot Summarization
Published 2019“…The objective of this work is to improve our previous action key frames extraction algorithm (AKF) by adapting a threshold which selects action key frames as final key frames. …”
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking
Published 2016“…This algorithm of capsule images can be clinically very useful as it can discriminate between normal and abnormal frame. …”
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Ulcer detection and classification of wireless capsule endoscopy images using RGB masking
Published 2016“…This algorithm of capsule images can be clinically very useful as it can discriminate between normal and abnormal frame. …”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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802.11 MAC layer sniffer using spoof detection algorithm / Azwan Abdul Satar
Published 2007“…The wireless sniffer implements sequence number-based spoofing detection algorithm in its processing. The information provided on both security and connectivity problem of wireless network can be generated by sniffing real-time frames capture using wireless adaptor or automation of log analysis on static pcap file. …”
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Thesis -
20
Automated threshold detection for object segmentation in colour image
Published 2016“…The procedure starts with selection of optimal RGB channel. Then H(•) algorithm is applied for automated threshold detection to convert the image frames into grayscale image. …”
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