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Aviad Aberdam
Also published under:
Affiliation
AWS AI Labs
Topic
Visual Features,Decoding,Image Captioning,Image Encoder,Image Texture,Inference Time,Integration Points,Language Model,Optical Character Recognition,Visual Model,Visual Question Answering,Visual Understanding,Additive Noise,Attention Heads,Attention Mechanism,Auxiliary Loss,Benchmark,Bias Values,Blocking Layer,Bounding Box,Cardinality,Combination Of Atoms,Computational Analysis,Consistent Improvement,Constant Bias,Context-aware,Contralateral,Convergence Rate,Dataset Bias,Design Choices,Diagonal Elements,Diverse Tasks,Early Fusion,Encoder Layer,Encoder-decoder Model,Encoding Stage,Extensive Experiments,Feed-forward Layer,Field Of Analysis,Fine-tuned,Gaussian Noise,Global Features,Ground Truth For Training,Higher Layers,Identity Matrix,Image Features,Image Information,Image Inpainting,Information Questions,Information Streams,
Biography
Aviad Aberdam received the BSc degree from the Department of Electrical Engineering, Technion, Israel, in 2017. He is currently working toward the PhD degree at the Technion, supervised by Michael Elad. His research interests include machine learning, optimization and signal and image processing, in particular inverse problems and sparse representations.