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Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero
Detecting Ai Generated Text Using Neural Networks, Jesus Guerrero
Masters Theses
For humans, distinguishing machine generated text from human written text is men- tally taxing and slow. NLP models have been created to do this more effectively and faster. But, what if some adversarial changes have been added to the machine generated text? This thesis discusses this issue and text detectors in general.
The primary goal of this thesis is to describe the current state of text detectors in research and to discuss a key adversarial issue in modern NLP transformers. To describe the current state of text detectors a Systematic Literature Review was done on 50 relevant papers to machine-centric …
Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara
Computer Vision In Adverse Conditions: Small Objects, Low-Resoltuion Images, And Edge Deployment, Raja Sunkara
Masters Theses
"Computer vision based on deep learning is an essential field that plays a significant role in object detection, image classification, semantic segmentation, instance segmentation, and other applications. However, these models face significant challenges in adverse conditions, such as small objects, low-resolution images, and edge deployment. These challenges limit the accuracy and efficiency of computer vision algorithms, making it difficult to obtain reliable results.
The primary objective of this thesis is to assess the performance of deep learning- based computer vision models in challenging conditions and provide viable solutions to overcome the obstacles. The study will specifically address three key challenges, …