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Automatic Pain Assessment Through Facial Expressions, Ilham Seladji
Automatic Pain Assessment Through Facial Expressions, Ilham Seladji
Theses
Pain is a strong symptom of diseases. Being an involuntary unpleasant feeling, it can be considered as a reliable indicator of health issues. Pain has always been expressed verbally, but in some cases, traditional patient self-reporting is not efficient. On one side, there are patients who have neurological disorders and cannot express themselves accurately, as well as patients who suddenly lose consciousness due to an abrupt faintness. On another side, medical staff working in crowded hospitals need to focus on emergencies and would opt for the automation of the task of looking after hospitalized patients during their entire stay, in …
Effective Activation Functions For Homomorphic Evaluation Of Deep Neural Networks, Srinath Obla
Effective Activation Functions For Homomorphic Evaluation Of Deep Neural Networks, Srinath Obla
Theses
CryptoNets and subsequent work have demonstrated the capability of homomorphic encryption (HE) in the applications of private artificial intelligence (AI). While convolutional neural networks (CNNs) are primarily composed of linear functions which can be homomorphically evaluated, layers such as the activation layer are non-linear and cannot be homomorphically evaluated. One of the most commonly used alternatives is approximating these non-linear functions using low-degree polynomials. However, it is difficult to generate efficient approximations and often, dataset specific improvements are required. This thesis presents a systematic method to construct HE-friendly activation functions for CNNs. We first determine the key properties in a …
Self-Supervision Initialization For Semantic Segmentation Networks, Kenneth Alexopoulos
Self-Supervision Initialization For Semantic Segmentation Networks, Kenneth Alexopoulos
Theses
Convolutional neural networks excel at extracting features from signals. These features are able to be utilized for many downstream tasks. These tasks include object recognition, object detection, depth estimation, pixel level semantic segmentation, and more. These tasks can be used for applications such as autonomous driving where images captured by a camera can be used to give a detailed understanding of the scene. While these models are impressive, they can fail to generalize to new environments. This forces the cumbersome process of collecting images from multifarious environments and annotating them by hand. Annotating thousands or millions of images is both …
Deepfakes Generation Using Lstm Based Generative Adversarial Networks, Akhil Santha
Deepfakes Generation Using Lstm Based Generative Adversarial Networks, Akhil Santha
Theses
Deep learning has been achieving promising results across a wide range of complex task domains. However, recent advancements in deep learning have also been employed to create software which causes threats to the privacy of people and national security. One among them is deepfakes, which creates fake images as well as videos that cannot be detected as forgeries by humans. Fake speeches of world leaders can even cause threat to world stability and peace. Apart from the malicious usage, deepfakes can also be used for positive purposes such as in films for post dubbing or performing language translation. This latter …
Design Of Hardware Cnn Accelerators For Audio And Image Classification, Rohini Jayachandre Gillela
Design Of Hardware Cnn Accelerators For Audio And Image Classification, Rohini Jayachandre Gillela
Theses
Ever wondered how the world was before the internet was invented? You might soon wonder how the world would survive without self-driving cars and Advanced Driver Assistance Systems (ADAS). The extensive research taking place in this rapidly evolving field is making self-driving cars futuristic and more reliable. The goal of this research is to design and develop hardware Convolutional Neural Network (CNN) accelerators for self-driving cars, that can process audio and visual sensory information. The idea is to imitate a human brain that takes audio and visual data as input while driving. To achieve a single die that can process …