Search Results for author:
Found 9 papers, 2 papers with code
Deep neural network-based detection of counterfeit products from smartphone images
Counterfeit products such as drugs and vaccines as well as luxury items such as high-fashion handbags, watches, jewelry, garments, and cosmetics, represent significant direct losses of revenue to legitimate manufacturers and vendors, as well as indirect costs to societies at large.
Preserving Empirical Probabilities in BERT for Small-sample Clinical Entity Recognition
Named Entity Recognition (NER) encounters the challenge of unbalanced labels, where certain entity types are overrepresented while others are underrepresented in real-world datasets.
Joint Stream: Malignant Region Learning for Breast Cancer Diagnosis
Early diagnosis of breast cancer (BC) significantly contributes to reducing the mortality rate worldwide.
A Large-scale Multi Domain Leukemia Dataset for the White Blood Cells Detection with Morphological Attributes for Explainability
The prognosis of leukemia is challenging without the morphological information of White Blood Cells (WBC) and relies on the accessibility of expensive microscopes and the availability of hematologists to analyze Peripheral Blood Samples (PBS).
Ranked #1 on
Domain Adaptation
on LeukemiaAttri
A survey of the Vision Transformers and their CNN-Transformer based Variants
This survey presents a taxonomy of the recent vision transformer architectures and more specifically that of the hybrid vision transformers.
Classifying Text-Based Conspiracy Tweets related to COVID-19 using Contextualized Word Embeddings
The FakeNews task in MediaEval 2022 investigates the challenge of finding accurate and high-performance models for the classification of conspiracy tweets related to COVID-19.
Real-time Speech Emotion Recognition Based on Syllable-Level Feature Extraction
A set of syllable-level formant features is extracted and fed into a single hidden layer neural network that makes predictions for each syllable as opposed to the conventional approach of using a sophisticated deep learner to make sentence-wide predictions.
DeepCFD: Efficient Steady-State Laminar Flow Approximation with Deep Convolutional Neural Networks
Computational Fluid Dynamics (CFD) simulation by the numerical solution of the Navier-Stokes equations is an essential tool in a wide range of applications from engineering design to climate modeling.
Brain MRI Segmentation using Rule-Based Hybrid Approach
Performance of these classifiers is investigated over different images of brain MRI and the variation in the performance of these classifiers is observed for different brain tissues.
