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The level of accuracy in predicting is the key in conducting forex trading activities in gaining profits. Some predictions are made only by using historical currency data to be predicted, this makes predictions less accurate because they do not consider external influences. This study examines external factors that can influence the results of predictions, by looking for the relationship between the value of indices such as NTFSE and S & P 500 and the value of commodities such as gold and...
Topics: CNN, Commodities, Deep learning, Forex, Indices
Miscellaneous Contributed Journals and Academic Newsletters
by Barlian Khasoggi, Ermatita, Samsuryadi
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The introduction of a modern image recognition that has millions of parameters and requires a lot of training data as well as high computing power that is hungry for energy consumption so it becomes inefficient in everyday use. Machine Learning has changed the computing paradigm, from complex calculations that require high computational power to environmentally friendly technologies that can efficiently meet daily needs. To get the best training model, many studies use large numbers of...
Topics: CNNs, Deep learning, Image recognition, MobileNet, Tensorflow
Miscellaneous Contributed Journals and Academic Newsletters
by Nurul FatihahSahidan, Ahmad Khairi Juha, Norasiah Mohammad, Zaidah Ibrahim
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This paper presents flower and leaf recognition for plant identification using Convolutional Neural Network (CNN). In this study, the performance of CNN for plant identification using images of the leaves, flowers and a combination of both are investigated. Two publicly available datasets, namely Folio leaf dataset and Flower Recognition dataset, have been used for the training and testing purposes. CNN has been proven to produce excellent results for object recognition but its performance can...
Topics: CNN, Deep learning, Flower recognition, Leaf recognition
Miscellaneous Contributed Journals and Academic Newsletters
by Muhaafidz Md Saufi, Mohd Afiq Zamanhuri, Norasiah Mohammad, Zaidah Ibrahim
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The advantage of deep learning is that the analysis and learning of massive amounts of unsupervised data make it a beneficial tool for Big Data analysis. Convolution Neural Network (CNN) is a deep learning method that can be used to classify image, cluster them by similarity, and perform image recognition in the scene. This paper conducts a comparative study between three deep learning models, which are simple-CNN, AlexNet and GoogLeNet for Roman handwritten character recognition using Chars74K...
Topics: AlexNet, CNN, Deep Learning, GoogLeNet, Handwritten Digit Recognition
Miscellaneous Contributed Journals and Academic Newsletters
by Nurul Fatihah Sahidan, Ahmad Khairi Juha, Zaidah Ibrahim
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This paper presents the evaluation of basic Convolutional Neural Network (CNN) and Bag of Features (BoF) for Leaf Recognition. In this study, the performance of basic CNN and BoF for leaf recognition using a publicly available dataset called Folio dataset has been investigated. CNN has proven its powerful feature representation power in computer vision. The same goes with BoF where it has set new performance standards on popular image classification benchmarks and has achieved scalability...
Topics: Bag of features, CNN, Deep learning, Leaf recognition
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Ateqah Binti Mat Kasim, Nur Hidayah Binti Abd Rahman, Zaidah Ibrahim, Nur Nabilah Abu Mangshor
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Face recognition is one of the well studied problems by researchers in computer visions. Among the challenges of this task are the occurrence of different facial expressions like happy or sad, and different views of the images such as front and side views. This paper experiments a publicly available dataset that consists of 200,000 images of celebrity faces. Deep Learning technique is gaining its popularity in computer vision and this paper applies this technique for face recognition problem....
Topics: AlexNet, Convolutional neural network, Deep learning, Face recognition, GoogLeNet
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Azmina Rahmad, Muhammad Amir As’ari, Nurul Fathiah Ghazali, Norazman Shahar, Nur Anis Jasmin Sufri
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Sport performance analysis which is crucial in sport practice is used to improve the performance of athletes during the games. Many studies and investigation have been done in detecting different movements of player for notational analysis using either sensor based or video based modality. Recently, vision based modality has become the research interest due to the vast development of video transmission online. There are tremendous experimental studies have been done using vision based modality...
Topics: Action recognition, Deep learning, Sport performance analysis, Video based modality
Miscellaneous Contributed Journals and Academic Newsletters
by Fadhlan Hafizhelmi Kamaru Zaman, Juliana Johari, Ahmad Ihsan Mohd Yassin
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Face verification focuses on the task of determining whether two face images belong to the same identity or not. For unrestricted faces in the wild, this is a very challenging task. Besides significant degradation due to images that have large variations in pose, illumination, expression, aging, and occlusions, it also suffers from large-scale ever-expanding data needed to perform one-to-many recognition task. In this paper, we propose a face verification method by learning face similarities...
Topics: Face verification, Face similarities, Unrestricted face, Face recognition, Deep learning
Miscellaneous Contributed Journals and Academic Newsletters
by Siti Aisyah Mohamed, Muhaini Othman, Mohd Hafizul Afifi
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The evolution of Artificial Neural Network recently gives researchers an interest to explore deep learning evolved by Spiking Neural Network clustering methods. Spiking Neural Network (SNN) models captured neuronal behaviour more precisely than a traditional neural network as it contains the theory of time into their functioning model [1]. The aim of this paper is to reviewed studies that are related to clustering problems employing Spiking Neural Networks models. Even though there are many...
Topics: Clustering, Deep learning, Machine learning, Spiking neural network, Temporal data
Miscellaneous Contributed Journals and Academic Newsletters
by Mohd Hanafi Ahmad Hijazi, Leong Qi Yang, Rayner Alfred, Hairulnizam Mahdin, Razali Yaakob
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Tuberculosis (TB) is one of the deadliest infectious disease in the world. TB is caused by a type of tubercle bacillus called Mycobacterium Tuberculosis. Early detection of TB is pivotal to decrease the morbidity and mortality. TB is diagnosed by using the chest x-ray and a sputum test. Challenges for radiologists are to avoid confused and misdiagnose TB and lung cancer because they mimic each other. Semi-automated TB detection using machine learning found in the literature requires...
Topics: Deep learning, Ensemble, Image classification, Medical image analysis, Tuberculosis detection
Miscellaneous Contributed Journals and Academic Newsletters
by Mohammed Nasser Al-Mhiqani, Rabiah Ahmad, Zaheera Zainal Abidin, Warusia Yassin, Aslinda Hassan, Ameera Natasha Mohammad
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Insider threat is a significant challenge in cybersecurity. In comparison with outside attackers, inside attackers have more privileges and legitimate access to information and facilities that can cause considerable damage to an organization. Most organizations that implement traditional cybersecurity techniques, such as intrusion detection systems, fail to detect insider threats given the lack of extensive knowledge on insider behavior patterns. However, a sophisticated method is necessary for...
Topics: Cyber security, Deep learning, Gated recurrent network, Insider Insider threat
Miscellaneous Contributed Journals and Academic Newsletters
by Nor Azizah Hitam, Amelia Ritahani Ismail
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Machine Learning is part of Artificial Intelligence that has the ability to make future forecastings based on the previous experience. Methods has been proposed to construct models including machine learning algorithms such as Neural Networks (NN), Support Vector Machines (SVM) and Deep Learning. This paper presents a comparative performance of Machine Learning algorithms for cryptocurrency forecasting. Specifically, this paper concentrates on forecasting of time series data. SVM has several...
Topics: Artificial Intelligence, Machine Learning, Support Vector Machines, Neural Networks, Deep Learning
Mobile and tablets are rapidly getting the chance to be basic device in the everyday life. Android has been the most well-known versatile working structure. Regardless, inferable from the open thought of Android, amount of malware is concealed in a broad number of kind applications in Android exhibits that really undermine Android security. Deep learning is another domain of AI explore that has expanded extending thought in artificial information. In this examination, we propose to relate the...
Topics: An android malware, Big data, Deep belief network, Deep learning, Security
Miscellaneous Contributed Journals and Academic Newsletters
by Mohd Hanafi Ahmad Hijazi, Leong Qi Yang, Rayner Alfred, Hairulnizam Mahdin, Razali Yaakob
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Tuberculosis (TB) is one of the deadliest infectious disease in the world. TB is caused by a type of tubercle bacillus called Mycobacterium Tuberculosis. Early detection of TB is pivotal to decrease the morbidity and mortality. TB is diagnosed by using the chest x-ray and a sputum test. Challenges for radiologists are to avoid confused and misdiagnose TB and lung cancer because they mimic each other. Semi-automated TB detection using machine learning found in the literature requires...
Topics: Deep learning, Ensemble, Image classification, Medical image analysis, Tuberculosis detection
Miscellaneous Contributed Journals and Academic Newsletters
by Nasibah Husna Mohd Kadir, Sharifah Nur Syafiqah Mohd Nur Hidayah, NorasiahMohammad, Zaidah Ibrahim
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This paper evaluates the recognition performance of Convolutional Neural Network (CNN) and Bag of Features (BoF) for multiple font digit recognition. Font digit recognition is part of character recognition that is used to translate images from many document-input tasks such as handwritten, typewritten and printed text. BoF is a popular machine learning method while CNN is a popular deep learning method. Experiments were performed by applying BoF with Speeded-up Robust Feature (SURF) and Support...
Topics: Bag of features (BoF), CNN, Deep learning, Font digit recognition
Miscellaneous Contributed Journals and Academic Newsletters
by Poonam G, Shashank B. N, Athri G Rao
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According to Global Adult Tobacco Survey 2016-17, 61.9% of people are quitting tobacco. The reason was the warnings displayed on the product covers, video clips, and advertisments. The focus of this paper is to automate the process of displaying warning messages in video clips. This paper explains the development of a system to automatically detect the smoking scenes using image recognition approach in video clips and then add the warning message to the viewer. The approach aims to detect the...
Topics: Deep learning, Faster R-CNN, Object detection, Smoking scene detection, Tensorflow
Miscellaneous Contributed Journals and Academic Newsletters
by Nur Azmina Rahmad, Nur Anis Jasmin Sufri, Nurul Hamizah Muzamil, Muhammad Amir As’ari
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Nowadays, coaches and sport analyst are concerning about sport performance analysis through sport video match. However, they still used conventional method which is through manual observation of the full video that is very troublesome because they might miss some meaningful information presence in the video. Several previous studies have discussed about tracking ball movements, identification of player based on jersey color and number as well as player movement detection in various type of...
Topics: Deep learning, Faster r-cnn, Player detection, Sport performance analysis, Video based modality