Face Recognition in Real-world Images

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Speech recognition-based applications upon the advancements in artificial intelligence play an essential role to transform most aspects of modern life. However, speech recognition in real-life conditions (e.g., in the presence of overlapping speech, varyin ...

State-of-the-art (SOTA) face recognition systems generally use deep convolutional neural networks (CNNs) to extract deep features, called embeddings, from face images. The face embeddings are stored in the system's database and are used for recognition of ...

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Face Recognition in Real-world Images

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Sparse Autoencoders for Speech Modeling and Recognition

Face Reconstruction Fromdeep Facial Embeddings Using A Convolutional Neural Network

Contrasting action and posture coding with hierarchical deep neural network models of proprioception

Regularization of polynomial networks for image recognition

From Undercomplete to Sparse Overcomplete Autoencoders to Improve LF-MMI Speech Recognition

A Virtual Simulation-Pilot Agent for Training of Air Traffic Controllers

Variational Methods For Continuous-Domain Inverse Problems: the Quest for the Sparsest Solution

Natural-Looking Adversarial Examples From Freehand Sketches

Regularization of polynomial networks for image recognition

The spectral bias of polynomial neural networks

Towards learning-based denoising of light fields

Indexing Protected Deep Face Templates by Frequent Binary Patterns

Cross-resolution Face Recognition via Identity-Preserving Network and Knowledge Distillation

On combining denoising with learning-based image decoding

Transfer learning application of self-supervised learning in ARPES

Improving Object Detection under Domain Shifts

A Two-Step Approach To Leverage Contextual Data: Speech Recognition In Air-Traffic Communications

Discriminative clustering with representation learning with any ratio of labeled to unlabeled data

A multimodal measurement of the impact of deepfakes on the ethical reasoning and affective reactions of students