activity
20222024
most citedPrecise Single-stage Detector

27 citations · 59 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CV2024

Saliency-Based diversity and fairness Metric and FaceKeepOriginalAugment: A Novel Approach for Enhancing Fairness and Diversity

Teerath Kumar, Alessandra Mileo, Malika Bendechache

Data augmentation has become a pivotal tool in enhancing the performance of computer vision tasks, with the KeepOriginalAugment method emerging as a standout technique for its inte…

cs.CV2024

FaceSaliencyAug: Mitigating Geographic, Gender and Stereotypical Biases via Saliency-Based Data Augmentation

Teerath Kumar, Alessandra Mileo, Malika Bendechache

Geographical, gender and stereotypical biases in computer vision models pose significant challenges to their performance and fairness. {In this study, we present an approach named…

cs.CV2024

OxML Challenge 2023: Carcinoma classification using data augmentation

Kislay Raj, Teerath Kumar, Alessandra Mileo +1

Carcinoma is the prevailing type of cancer and can manifest in various body parts. It is widespread and can potentially develop in numerous locations within the body. In the medica…

cs.CV2024★ 1 cited

KeepOriginalAugment: Single Image-based Better Information-Preserving Data Augmentation Approach

Teerath Kumar, Alessandra Mileo, Malika Bendechache

Advanced image data augmentation techniques play a pivotal role in enhancing the training of models for diverse computer vision tasks. Notably, SalfMix and KeepAugment have emerged…

cs.SD2023★ 4 cited

AudRandAug: Random Image Augmentations for Audio Classification

Teerath Kumar, Muhammad Turab, Alessandra Mileo +2

Data augmentation has proven to be effective in training neural networks. Recently, a method called RandAug was proposed, randomly selecting data augmentation techniques from a pre…

cs.CV2023★ 15 cited

Image Data Augmentation Approaches: A Comprehensive Survey and Future directions

Teerath Kumar, Alessandra Mileo, Rob Brennan +1

Deep learning (DL) algorithms have shown significant performance in various computer vision tasks. However, having limited labelled data lead to a network overfitting problem, wher…

eess.SP2023★ 7 cited

Understanding EEG signals for subject-wise Definition of Armoni Activities

Kislay Raj, Aditya Singh, Abhishek Mandal +2

In a growing world of technology, psychological disorders became a challenge to be solved. The methods used for cognitive stimulation are very conventional and based on one-way com…

cs.CV2022★ 27 cited

Precise Single-stage Detector

Aisha Chandio, Gong Gui, Teerath Kumar +5

There are still two problems in SDD causing some inaccurate results: (1) In the process of feature extraction, with the layer-by-layer acquisition of semantic information, local in…

eess.IV2022★ 1 cited

Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets

Sidra Aleem, Teerath Kumar, Suzanne Little +3

Over the years, the paradigm of medical image analysis has shifted from manual expertise to automated systems, often using deep learning (DL) systems. The performance of deep learn…

cs.SD2022★ 4 cited

Investigating Multi-Feature Selection and Ensembling for Audio Classification

Muhammad Turab, Teerath Kumar, Malika Bendechache +1

Deep Learning (DL) algorithms have shown impressive performance in diverse domains. Among them, audio has attracted many researchers over the last couple of decades due to some int…