Browsing by Subject "Deep learning"

An agile project management supporting approach for estimating story points in user stories

Wanigasooriya Arachchi, KJ; Amalraj, CRJ [Conference-Full-text]

While significant research has been conducted on software analytics for effort estimation in traditional software projects, limited attention has been given to estimation in agile projects, particularly in estimating ...

Analyze the visual quality of roads utilizing deep learning algorithms and street view images

Wickramasinghe, P; Jayasinghe, A [Conference-Full-text]

Visual quality of roads is one of very important factor in road design. However, in current practice objective analysis and judgment is lacking and mostly utilized subjective judgment to evaluate the visual quality of road. ...

The application of convolutional neural network in the context of Tamil handwritten character recognition

Thuvarakan, P; Kowreesan, P; Jeyarooban, S; Janotheepan, M; Ekanayake, EMUWJB [Conference-Full-text]

This research paper presents an in-depth investigation into the application of Convolutional Neural Networks (CNNs) for Tamil handwritten character recognition. We explore existing research, methodologies, and ...

Augmented reality based breadboard circuit building guide application

Thiwanka, N; Chamodika, U; Priyankara, L; Sumathipala, S; Weerasuriya, GT [Conference-Full-text]

Building circuits on breadboards is an activity which requires a lot of attention and thinking. If there is a way to guide this process by using modern technologies, the learning process can be made more effective and ...

Characterizing fracture stress of defective graphene samples using shallow and deep artificial neural networks

Dewapriya, MAN; Rajapakse, RKND; Dias, WPS [Article-Full-text]

Advanced machine learning methods could be useful to obtain novel insights into some challenging nanomechanical problems. In this work, we employed artificial neural networks to predict the fracture stress of defective ...

A deep learning ensemble hate speech detection approach for sinhala tweets

Munasinghe, S; Thayasivam, U [Conference-Full-text]

We live in an era where social media platforms play a key role in society. These platforms support most of the native languages and this has enabled people to express their opinions conveniently. Also, it is very common ...

Enhanced sentiment extraction architecture for social media content analysis using capsule networks

Demotte, P; Wijegunarathna, K; Meedeniya, D; Perera, I [Article-Full-text]

Recent research has produced efficient algorithms based on deep learning for text-based analytics. Such architectures could be readily applied to text-based social media content analysis. The deep learning techniques, ...

Enhanced sentiment extraction architecture for social media content analysis using capsule networks

Demotte, P; Wijegunarathna, K; Meedeniya, D; Perera, I [Article-Full-text]

Recent research has produced efficient algorithms based on deep learning for text-based analytics. Such architectures could be readily applied to text-based social media content analysis. The deep learning techniques, which ...

Explainable ai techniques for deep convolutional neural network based plant disease identification

Kiriella, S; Fernando, S; Sumathipala, S; Udayakumara, EPN [Conference-Full-text]

Deep learning-based computer vision has shown improved performance in image classification tasks. Due to the complexities of these models, they have been referred as opaque models. As a result, users need justifications ...

Land-use change dynamics and automated feature extraction using high-resolution satellite imagery

Dey, M; Prakash, PS; Chandrashekar, CM; Aithal, BH [Conference-Full-text]

The mapping of urban landscapes is a challenging task due to their dense and diverse characteristics. The changing urban environment with developing infrastructure demands constant updates and accurate extraction techniques. ...

Multimedia big data platform with a deep learning approach for flood emergency management

Weerasinghe, IDTT; Jayasena, KPN [Conference-Full-text]

Flood emergency management has been a major issue in the last few decades as it can disrupt human lives as well as the economy and property damage. A flood occurs when the overflow of water that melts relatively dry land. ...

Novel deep learning and GIS-based approach for road inventory survey

Wanniarachchi, S; Lindamullage, H; Jayasinghe, A; Bandara, S [Conference-Full-text]

The existing road inventory preparation methods are time-consuming, labor-intensive, inefficient, and there is no acceptable method for 3D urban visualisation. Accordingly, the study proposed a new cost-effective application ...

Pose estimation of a robot arm from a single camera

Sithamparanathan, K; Rajendran, S; Thavapirakasam, P; Abeykoon, AMHS [Conference-Full-text]

This paper describes a vision based deep learning approach to estimate the pose of a robot arm from a single camera input, without any depth information. Conventionally, pose of robot arm is determined using encoders ...

Sentiment analysis of tamil-english code-switched text on social media using sub-word level lstm

Raveendirarasa, V; Amalraj, CRJ [Conference-Full-text]

Social media are the ultimate platforms to express the opinion and to facilitate the creation and sharing of information, ideas, career interests and other forms of expression via virtual communities and networks. Analysing ...

A Smart telemedicine system with deep learning to manage diabetic retinopathy and foot ulcers

Wijesinghe, I; Gamage, C; Perera, I; Chitraranjan

Artificial intelligence in combination with modern technologies including medical screening devices has the potential to deliver better management services to deal with chronic diseases with higher accuracy, efficiency, ...

Text summarization for tamil online sports news using nlp

Priyadharshan, T; Sumathipala, S [Conference-Full-text]

Text summarization plays an important problem in natural language understanding and information retrieval. Automatic text summarization get much more attention by people presently because it is efficiently and effectively ...

Transformers in single object tracking

Kugarajeevan, J; Kokul, T; Ramanan, A; Fernando, S [Article-Full-text]

Single-object tracking is a well-known and challenging research topic in computer vision. Over the last two decades, numerous researchers have proposed various algorithms to solve this problem and achieved promising results. ...

Use of deep learning as an alternative to manual counts in Sri Lanka

Herath, HMOK; Sivakumar, T [Conference-Abstract]

Maintaining a count of vehicles on roads by vehicle category is important for purposes of traffic monitoring, analysis and prediction. To overcome disadvantages in manual traffic counts, this study focuses on computer ...

Using CNN to identify the condition of edible fish

Mahendran, R; Seneviratne, GP [Conference-Abstract]

Evaluating the edibility of fish by it’s freshness is an essential process for the fisheries industry as it contributes to customers’ health and the taste of food. In general, identifying freshness of fish is a difficult ...

Video colorization dataset and benchmark

Abeysinghe, C; Wijesinghe, T; Wijesinghe, C; Jayathilake, L; Thayasivam, U [Conference-Abstract]

Video colorization is the process of assigning realistic, plausible colors to a grayscale video. Compared to its peer, image colorization, video colorization is a relatively unexplored area in computer vision. Most of ...

Browsing by Subject "Deep learning"

Browsing by Subject "Deep learning"

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