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94 articles for “Deep Neural Networks”

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Research ArticleOpen accessIn the abstractPerformance Evaluation of Deep Learning Networks on Printed Odia CharactersSanjibani Sudha Pattanayak, Sateesh Kumar Pradhan, Ramesh Chandra MalikDeep machine learning includes a series of layers to mimic the working of the human brain for taking a decision. Deep learning networks have shown good results in character recognition in the past. This paper evaluates the performance of different deep learning networks like Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) based recurrent neural network and Convolutional LSTM on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractGoogleNet CNN Neural Network towards Chest CT-Coronavirus Medical Image ClassificationNesreen Alsharman, Ibrahim JawarnehIn the end of the year 2019 and the beginning of the year 2020, the world was overwhelmed by a medical pandemic that was not previously seen which is known Covid-19 (Coronavirus). Coronavirus (CoV) is a large family of viruses that cause illness ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS-CoV) and … …Journal of Computer Science, Vol. 16, Issue 5 · 14 May 2020 · 9,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultipatch-GLCM for Texture Feature Extraction on Classification of the Colon Histopathology Images using Deep Neural Network with GPU AccelerationToto Haryanto, Adib Pratama, Heru Suhartanto et al.Cancer is one of the leading causes of death in the world. It is the main reason why research in this field becomes challenging. Not only for the pathologist but also from the view of a computer scientist. Hematoxylin and Eosin (H&E) images are the most common modalities used by the pathologist for cancer detection. The status of cancer with … …Journal of Computer Science, Vol. 16, Issue 3 · 5 Mar 2020 · 9,215 accessesView PDFCite
Research ArticleOpen accessIn the abstractLong Short-Term Memory Model for Classification of English-PtBR Cross-Lingual Hate SpeechThiago D. Bispo, Hendrik T. Macedo, Flávio de O. Santos et al.Automatic and accurate recognition of hate speech is a difficult job. In addition to the inherent ambiguity of the natural language, deep understanding of the linguistic structure is imperative. Usually, discriminatory discourse does not make use of typical expressions and often abuse of sarcasm. Good knowledge of world and assessment of context are thus highly demanded. Several approaches have been … …Journal of Computer Science, Vol. 15, Issue 10 · 1 Nov 2019 · 7,338 accessesView PDFCite
Research ArticleOpen accessIn the abstractEfficient Music Auto-Tagging with Convolutional Neural NetworksShaleen Bengani, S. Vadivel, J. Angel Arul JothiTechnology is revolutionizing the way in which music is distributed and consumed. As a result, millions of songs are instantly available to millions of people, on the Internet. This has created the need for novel music search and discovery services. Music is often searched using descriptive keywords, or tags, based on the content of the song. Hence, one very important … …Journal of Computer Science, Vol. 15, Issue 8 · 27 Aug 2019 · 7,841 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 · 8,987 accessesView PDFCite
Research ArticleOpen accessIn the abstractVehicle Detection in Aerial Traffic MonitoringDmitry Sincha, Mikhail Chervonenkis, Pavel SkribtsovThis work describes a cascade detection of vehicles in Unmanned Aerial Vehicle (UAV) images and videos. There are some new approaches used in the detection. In particular, the Region of Interest (ROI) search is not only based on GIS and navigation data, but also employs visual method based on rapid image segmentation and road detection. The work also suggests doing … …American Journal of Applied Sciences, Vol. 13, Issue 1 · 11 Jan 2016 · 7,925 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite
Review ArticleOpen accessAll words, across the recordA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite