Living in the modern age of technology where there are high slogans of face analytics, data mining, social media analysis, Kinship verification finds its way from the automatic tagging of pictures,videos to the surveillance,security,human trafficking control and many more applicable areas. Automated Kinship Verification answers the question that the two individuals are blood relatives or […]
Social media has seen a boom in recent years, with its users growing worldwide. The ubiquitous nature of social media has made it a useful tool to extract useful information regarding disasters. As in case of any disaster, people upload data related to the disaster on social media which can be very useful in the […]
Reinforcement learning generates policies based on reward functions, hyper-parameters. Slight changes in these can significantly affect results. The lack of documentation and reproducibility in Reinforcement learning research makes it difficult to replicate once-deduced strategies. While previous research has identified strategies using grounded maneuver, there is limited work in the more complex environments. The agents in […]
Research in the field of text to image generation has shown incredible momentum owing to the availability of more powerful natural language processing (NLP) models and generative networks. The quality of data representation learned by the generative models acts as a determining factor in the success of these models. Self-supervised learning augments the generative power […]
The model combines a SincNet layer, which uses band-pass filters based on the sinc function to extract audio features, with CNN and LSTM layers to capture spatial and temporal dynamics in speech signals. By integrating these components, the proposed model aims to learn features from raw audio and effectively handle sequential data. The study’s objectives include developing and evaluating the proposed model for dysarthria detection, comparing its performance with existing models, and examining factors contributing to its success. Additionally, the model’s robustness and generalization capabilities are tested on publicly available TORGO datasets and achieved an overall accuracy of 99%.
Islamophobia or anti-Muslim antagonism is one prepotent yet dilapidated form of racism in our today’s world. The last couple of years have witnessed an immense surge in Islamophobic hate speech on social media nurturing and progressing violence and prejudice against Muslims and Islam. A growingly frequent expression of online hate speech is multimodal (text + […]
This thesis investigates the dynamics of crowdfunding success in Kickstarter’s technology category using a blend of network analysis and machine learning. By sourcing a comprehensive dataset from Webrobots.io, which includes detailed monthly data dumps of Kickstarter projects, this study focuses on United States (U.S.)-based technology projects to uncover patterns and factors contributing to successful crowdfunding […]
A cross-platform mobile application that provides a comprehensive set of features to users using advanced AI and ML techniques.
To implement an AI-based GDM screening and outcome prediction platform for a diverse demographic population of South Asia by selecting Pakistan as a base case study.
Our approach involves a fusion of deformable style transfer (DST), an optimization-centric technique that harmonizes the texture and geometry of a given content image to closely align with a chosen style image. This methodology is coupled with diffusion model inpainting, which is applied to content images originating from Calliar: an online dataset featuring handwritten Arabic calligraphy. Diverging from previous generative art methodologies, our approach presents aesthetically pleasing results, all the while preserving the integrity and structure of the Arabic script.