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145 articles for “Deep Learning Models”
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Research ArticleOpen accessIn the abstractGrasshopper Optimization Algorithm-Generative Adversarial Network for Lung Cancer Detection and ClassificationSukruth Gowda, A JayachandranLung cancer is one of the most dangerous deadly diseases for individuals worldwide. Thus, the survival rate is low due to the difficulty in detecting lung cancer at advanced stages like symptoms; thus, prominence for early diagnosis is important. The detection and treatment of lung cancer is having great importance for early diagnosis. The existing Convolution Neural Network (CNN) based … …Journal of Computer Science, Vol. 18, Issue 3 · 9 Apr 2022 · 6,579 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifications of Skull Fractures using CT Scan Images via CNN with Lazy Learning ApproachMd Moniruzzaman Emon, Tareque Rahman Ornob, Moqsadur RahmanClassification of skull fracture is a challenging task for both radiologists and researchers. Skull fractures result in broken pieces of bone, which can cut into the brain and cause bleeding and other injury types. So it is vital to detect and classify the fracture very early. In real world, often fractures occur at multiple sites. This makes it harder to … …Journal of Computer Science, Vol. 18, Issue 3 · 15 Mar 2022 · 9,012 accessesView PDFCite
Research ArticleOpen accessIn the abstractFace Verification for Person Re-Identification from Surveillance Camera and Drone-based VideosVimala Mathew, K. Ramesh, Tom Toby, Anu Mary ChackoPerson re-identification in surveillance camera videos is attracting widespread interest due to its increasing number of applications. It is being applied in the field of security, healthcare, product manufacturing, product sales and more. Though there are a variety of methods to do person re-identification, face verification-based methods are very much effective. In this study, a deep learning framework to perform … …Journal of Computer Science, Vol. 17, Issue 7 · 28 Jul 2021 · 7,322 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning and Deep Learning for Phishing Email Classification using One-Hot EncodingSikha Bagui, Debarghya Nandi, Subhash Bagui, Robert Jamie WhiteRepresentation of text is a significant task in Natural Language Processing (NLP) and in recent years Deep Learning (DL) and Machine Learning (ML) have been widely used in various NLP tasks like topic classification, sentiment analysis and language translation. Until very recently, little work has been devoted to semantic analysis in phishing detection or phishing email detection. The novelty of … …Journal of Computer Science, Vol. 17, Issue 7 · 23 Jul 2021 · 10,940 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,973 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeafsnapNet: An Experimentally Evolved Deep Learning Model for Recognition of Plant Species based on Leafsnap Image DatasetEmmanuel Adetiba et al.Plants are very important living organisms on earth because humans and animals depend on them for nutrition, oxygen, medicine and balance in the ecosystem. Therefore, plant species recognition is critical to the improvement of agricultural productivity, mitigation of climate change and the discovery of new medicinal plants. However, species recognition has remained a difficult task even for trained botanists, because … …Journal of Computer Science, Vol. 17, Issue 3 · 1 Apr 2021 · 7,961 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvSVD++: A Hybrid Deep CF Recommender Model using Convolutional Neural NetworkMohamed Grida, Lamiaa Fayed, Mohamed HassanRecommender systems are powerful systems that give added value to business and corporation. They are relatively recent technology and they will only keep improving in the future. The most widely used algorithms for recommender systems are categorized into the traditional recommender and deep-based recommender system. The traditional recommendation algorithm suffers from sparse data that significantly degrades recommendation accuracy. The hybrid … …Journal of Computer Science, Vol. 16, Issue 12 · 13 Jan 2021 · 6,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Super-Resolution using Auto-Encoders with Parallel Skip-ConnectionsLisha Pulickal Purushothaman, Jayasree Vadakke KadangoteSuper-resolutionimages are highly desired when employed for numerous analytical purposes andobviously because of their superior attractive visual effect. To create aHigh-Resolution (HR) image from one or more Low-Resolution (LR) images, animage super-resolution technique is used. When dealing with naturalenvironments and settings, it is not always easy to access high-resolutionimages. The main barriers to the same are limitations in acquisition methods.In … …Journal of Computer Science, Vol. 18, Issue 11 · 11 Nov 2022 · 6,084 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractFarmer-Friendly Mobile Application for Automated Leaf Disease Detection of Real-Time Augmented Data Set using Convolution Neural NetworksRishiikeshwer B. S., T. Aswin Shriram, J. Sanjay Raju et al.In farming, crops are prone to a wide variety of diseases. The impact of sudden climatic change has adverse effects on their growth, providing incubation to harmful viruses and bacteria. Diseases to crops imply a significant negative impact on health, economy and livelihood of the human population. According to the data from the Food and Agricultural Organization (FAO), an average … …Journal of Computer Science, Vol. 16, Issue 2 · 24 Aug 2019 · 8,993 accessesView PDFCite