Deep learning is the foundation for various applications, including decision support, fraud detection, text categorization, machine translation, market research, and customer segmentation. Despite their widespread use, deep learning algorithms are frequently vulnerable to adversarial instances, in which legal inputs are manipulated in subtle and often invisible ways. Even the most complicated models may be tricked […]
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%.
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.
Descriptive and Predictive Analysis of infectious diseases
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.
Descriptive and Predictive Analysis of infectious diseases
Simulation of ASV with autonomous navigation and collision avoidance in any Simulation Software. Reinforcement Learning based trained algorithm is used.
Detecting hate speech is indispensable irrespective of the scale of use of language as it inflicts huge harm on society. This work presents a first resource for classifying the severity of hate speech besides classifying offensive and hate speech content. Current research mostly limits hate speech classification only to its primary categories such as racism, […]
Scope of the Project: The primary scope of the project is to provide real time river water level and speed to the main server via a remote embedded system. At the main server this information is stored, manipulated and graphs are generated to get a near to accurate flood prediction. System shall also provide flood […]
Humans while driving have a disadvantage of not always being attentive (whether it be changing the radio or of being tired etc.) while a computer, if trained, can always be fully attentive at detecting lanes. Driver support system is one of the most important feature of modern vehicles. This is to ensure driver safety and […]