Search Results for author: Adil Khan

Found 17 papers, 4 papers with code

ReFuSeg: Regularized Multi-Modal Fusion for Precise Brain Tumour Segmentation

no code implementations26 Aug 2023 Aditya Kasliwal, Sankarshanaa Sagaram, Laven Srivastava, Pratinav Seth, Adil Khan

This paper presents a novel multi-modal approach for brain lesion segmentation that leverages information from four distinct imaging modalities while being robust to real-world scenarios of missing modalities, such as T1, T1c, T2, and FLAIR MRI of brains.

Anatomy Lesion Segmentation +3

Not So Robust After All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks

no code implementations12 Aug 2023 Roman Garaev, Bader Rasheed, Adil Khan

This hypothesis suggests that training a DNN on a dataset consisting solely of robust features should produce a model resistant to adversarial attacks.

Adversarial Attack Attribute

Exploring Semantic Variations in GAN Latent Spaces via Matrix Factorization

1 code implementation23 May 2023 Andrey Palaev, Rustam A. Lukmanov, Adil Khan

Controlled data generation with GANs is desirable but challenging due to the nonlinearity and high dimensionality of their latent spaces.

Disentanglement

UATTA-ENS: Uncertainty Aware Test Time Augmented Ensemble for PIRC Diabetic Retinopathy Detection

1 code implementation6 Nov 2022 Pratinav Seth, Adil Khan, Ananya Gupta, Saurabh Kumar Mishra, Akshat Bhandari

Deep Ensemble Convolutional Neural Networks has become a methodology of choice for analyzing medical images with a diagnostic performance comparable to a physician, including the diagnosis of Diabetic Retinopathy.

Diabetic Retinopathy Detection

RepFair-GAN: Mitigating Representation Bias in GANs Using Gradient Clipping

no code implementations13 Jul 2022 Patrik Joslin Kenfack, Kamil Sabbagh, Adín Ramírez Rivera, Adil Khan

Fairness has become an essential problem in many domains of Machine Learning (ML), such as classification, natural language processing, and Generative Adversarial Networks (GANs).

Fairness

Bridging the Domain Gap for Stance Detection for the Zulu language

no code implementations6 May 2022 Gcinizwe Dlamini, Imad Eddine Ibrahim Bekkouch, Adil Khan, Leon Derczynski

This allows us to rapidly achieve similar results for stance detection for the Zulu language, the target language in this work, as are found for English.

Domain Adaptation Machine Translation +2

Class-incremental Learning using a Sequence of Partial Implicitly Regularized Classifiers

no code implementations4 Apr 2021 Sobirdzhon Bobiev, Adil Khan, Syed Muhammad Ahsan Raza Kazmi

In class-incremental learning, the objective is to learn a number of classes sequentially without having access to the whole training data.

Class Incremental Learning Incremental Learning

Hierarchical Transformer for Multilingual Machine Translation

no code implementations EACL (VarDial) 2021 Albina Khusainova, Adil Khan, Adín Ramírez Rivera, Vitaly Romanov

The choice of parameter sharing strategy in multilingual machine translation models determines how optimally parameter space is used and hence, directly influences ultimate translation quality.

Machine Translation Translation

Post-training Iterative Hierarchical Data Augmentation for Deep Networks

no code implementations NeurIPS 2020 Adil Khan, Khadija Fraz

Accordingly, the IHDA performs DA in a deep feature space, at level l, by transforming it into a distribution space and synthesizing new samples using the learned distributions for data points that lie in hard-to-classify regions, which is estimated by analyzing the neighborhood characteristics of each data point.

Activity Recognition Data Augmentation

Task-Oriented Language Grounding for Language Input with Multiple Sub-Goals of Non-Linear Order

1 code implementation27 Oct 2019 Vladislav Kurenkov, Bulat Maksudov, Adil Khan

In this work, we analyze the performance of general deep reinforcement learning algorithms for a task-oriented language grounding problem, where language input contains multiple sub-goals and their order of execution is non-linear.

reinforcement-learning Reinforcement Learning (RL)

SART - Similarity, Analogies, and Relatedness for Tatar Language: New Benchmark Datasets for Word Embeddings Evaluation

1 code implementation31 Mar 2019 Albina Khusainova, Adil Khan, Adín Ramírez Rivera

We evaluate state-of-the-art word embedding models for two languages using our proposed datasets for Tatar and the original datasets for English and report our findings on performance comparison.

Embeddings Evaluation Language Modelling

Open source platform Digital Personal Assistant

no code implementations11 Jan 2018 Denis Usachev, Azat Khusnutdinov, Manuel Mazzara, Adil Khan, Ivan Panchenko

In this paper we develop an open source DPA and smart home system as a 3-rd party extension to show the functionality of the assistant.

Human-Computer Interaction

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