Sökning: "Hossein Azizpour"

Visar resultat 1 - 5 av 6 avhandlingar innehållade orden Hossein Azizpour.

1. 1. Visual Representations and Models: From Latent SVM to Deep Learning

   Författare :Hossein Azizpour; Stefan Carlsson; Barbara Caputo; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Computer Vision; Machine Learning; Artificial Intelligence; Deep Learning; Learning Representation; Deformable Part Models; Discriminative Latent Variable Models; Convolutional Networks; Object Recognition; Object Detection; Computer Science; Datalogi;

   Sammanfattning : Two important components of a visual recognition system are representation and model. Both involves the selection and learning of the features that are indicative for recognition and discarding those features that are uninformative. LÄS MER

3. 2. Structured Representations for Explainable Deep Learning

   Författare :Federico Baldassarre; Hossein Azizpour; Josephine Sullivan; Kevin Smith; Hamed Pirsiavash; KTH; []
   Nyckelord :NATURVETENSKAP; NATURAL SCIENCES; Explainable AI; Deep Learning; Self-supervised Learning; Transformers; Graph Networks; Computer Vision; Explainable AI; Deep Learning; Self-supervised Learning; Transformers; Graph Networks; Computer Vision; Datalogi; Computer Science;

   Sammanfattning : Deep learning has revolutionized scientific research and is being used to take decisions in increasingly complex scenarios. With growing power comes a growing demand for transparency and interpretability. The field of Explainable AI aims to provide explanations for the predictions of AI systems. LÄS MER

4. 3. Robots That Understand Natural Language Instructions and Resolve Ambiguities

   Författare :Fethiye Irmak Dogan; Iolanda Leite; Hedvig Kjellström; Hossein Azizpour; David Traum; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; Datalogi; Computer Science;

   Sammanfattning : Verbal communication is a key challenge in human-robot interaction. For effective verbal interaction, understanding natural language instructions and clarifying ambiguous user requests are crucial for robots. In real-world environments, the instructions can be ambiguous for many reasons. LÄS MER

5. 4. Time, space and control: deep-learning applications to turbulent flows

   Författare :Luca Guastoni; Ricardo Vinuesa; Hossein Azizpour; Philipp Schlatter; Andrea Beck; KTH; []
   Nyckelord :TEKNIK OCH TEKNOLOGIER; ENGINEERING AND TECHNOLOGY; turbulence; deep learning; deep reinforcement learning; flow control; turbulens; djupinlärning; djupförstärkningsinlärning; flödeskontroll; Teknisk mekanik; Engineering Mechanics;

   Sammanfattning : In the present thesis, the application of deep learning and deep reinforcement learning to turbulent-flow simulations is investigated. Deep-learning models are trained to perform temporal and spatial predictions, while deep reinforcement learning is applied to a flow-control problem, namely the reduction of drag in an open channel flow. LÄS MER

7. 5. Breast cancer risk assessment and detection in mammograms with artificial intelligence

   Författare :Yue Liu; Kevin Smith; Hossein Azizpour; Fredrik Strand; Anders Eklund; KTH; []
   Nyckelord :MEDICIN OCH HÄLSOVETENSKAP; MEDICAL AND HEALTH SCIENCES; Mammography; AI; Breast cancer risk; Breast cancer detection; Mammografi; AI; Bröstcancerrisk; Upptäckt av bröstcancer; Datalogi; Computer Science;

   Sammanfattning : Breast cancer, the most common type of cancer among women worldwide, necessitates reliable early detection methods. Although mammography serves as a cost-effective screening technique, its limitations in sensitivity emphasize the need for more advanced detection approaches. LÄS MER